Emilien Ghomi
email: ghomi@lri.frgfaure@lri.fr

Guillaume Faure

Stéphane Huot
email: huot@lri.fr

Olivier Chapuis
email: chapuis@lri.frmbl@lri.fr

Michel Beaudouin-Lafon

Using Rhythmic Patterns as an Input Method

Keywords: ACM Classification H.5.2 [Information interfaces and presentation]: User Interfaces. -Graphical user interfaces Rhythm, taping, hotkeys, learning, patterns, Morse code

While interaction techniques that use the temporal dimension have been used for a long time, such as multiple clicks or spring-loaded widgets, more advanced uses of rhythmic patterns have received little attention in HCI. Using such temporal structures to convey information can be particularly useful in situations where the visual channel is overloaded or even not available. In this paper we introduce Rhythmic Interaction as the use of rhythms for input. We report the results of two experiments that show that (i) rhythmic patterns can be efficiently reproduced by novice users and recognized by computer algorithms, and (ii) rhythmic patterns can be memorized as efficiently as traditional shortcuts when associating them with visual commands. Overall, these results demonstrate the potential of Rhythmic Interaction and open the way to a richer repertoire of interaction techniques.

INTRODUCTION

Rhythm plays an important role in our everyday life. Temporal patterns are of course critical in experiencing music, but they also underlie periodic actions such as walking, breathing or chewing, and they are even necessary for understanding speech prosody. Rhythm is so deeply embedded in our experience of living that it can be used to cure some diseases such as stress or sleep disorders [START_REF] Sacks | Tales of Music and the Brain[END_REF].

While perceiving and reproducing rhythm is recognized as a fundamental human ability by physiologists and neuropsychologists, it is still underused as an interactive dimension in HCI. In common desktop environments, interaction relies heavily on manipulating graphical widgets, simple mouse clicks and keyboard shortcuts. This basic vocabulary, however, is often extended by using spatial or temporal features, as with mouse gestures or multiple clicks. Although the spatial dimension has been the focus of much HCI research on interaction techniques based on hand postures or gestures, e.g. [START_REF] Appert | Using strokes as command shortcuts: cognitive benefits and toolkit support[END_REF][START_REF] Baudel | Charade: Remote control of objects using free-hand gestures[END_REF][START_REF] Kurtenbach | User learning and performance with marking menus[END_REF], the temporal dimension has received little attention so far. We propose to use rhythm as an input method and introduce Rhythmic Interaction as a complementary way to control interactive systems. Rhythmic Interaction can be used in any event-driven environment for a variety of input modalities: clicking the mouse, hitting keyboard keys or a touch-sensitive surface, moving a motionsensing device, etc. However, it has competitive advantages for tactile screens, since it requires less screen space than gestural interaction and no visual attention [START_REF] Wobbrock | Tapsongs: tapping rhythm-based passwords on a single binary sensor[END_REF]. This article presents a first exploration of the design space of Rhythmic Interaction in order to address the following questions:

• Feasibility. Even if perceiving and performing rhythm is quite natural, are users able to reproduce, learn and memorize patterns? Can they use them to trigger commands?

• Interaction design. The number of possible rhythmic patterns is virtually infinite and they can be presented in several ways. Which patterns make sense for interaction and how to design a vocabulary? What feedback helps executing and learning patterns?

• Technical issues & Integration. Like most continuous highlevel input methods, e.g. voice, marks, gestures, Rhythmic Interaction relies on a recognizer to segment and interpret user input. How to design effective recognizers that do not require training?

In the rest of this paper, we survey related work and then define a framework for Rhythmic Interaction, narrowing the scope of our study to vocabularies of rhythmic patterns that are relevant in the context of HCI. Then, we report on two experiments where the patterns are rhythmic sequences of taps performed on a tactile trackpad to trigger commands. The first one tests the ability of novice users to reproduce individual patterns, while the second one compares the ability of users to memorize the association of commands to rhythmic patterns vs. keyboard shortcuts. We also describe the recognizers that we created for these two experiments, and draw some conclusions regarding the design of pattern vocabularies and appropriate feedback.

BACKGROUND & RELATED WORK

The literature in cognitive science has studied the perception, reproduction and use of rhythm from several perspectives: physiology, e.g., perception and action [START_REF] Glass | Synchronization and rhythmic processes in physiology[END_REF][START_REF] Macdougall | Marching to the beat of the same drummer: the spontaneous tempo of human locomotion[END_REF], knowledge and learning, e.g., language [START_REF] Petitto | Baby hands that move to the rhythm of language: hearing babies acquiring sign languages babble silently on the hands[END_REF], artistic applications, e.g., music [START_REF] Moelants | Preferred tempo reconsidered[END_REF], etc. Two major studies on the psychology of rhythm in music are reported by Fraisse [START_REF] Fraisse | Rhythm and tempo[END_REF] and by Clarke [START_REF] Clarke | Rhythm and timing in music[END_REF]. In this section, we give an overview of the literature in cognitive science that is most relevant to Rhythmic Interaction and then focus on the few studies of using time and rhythm to control interactive systems.

Rhythm in Music and Games

For musicians, rhythm is one of the most important features in music, together with melody and harmony. Many traditional forms of music combine simple rhythmic structures played in parallel to build up higher level aggregated rhythms, called "polyrhythms" [START_REF] Arom | African polyphony and polyrhythm: musical structure and methodology[END_REF]. From a cognitive point of view, these practices suggest that the cognitive load required to deal with an elementary rhythmic pattern is light enough to allow their combination in more complex structures.

Highly trained musicians are able to create and play an incredible amount of rhythmic variations. Simple patterns, however, can be reproduced by everyone, as illustrated by the success of popular musical games such as Guitar Hero, TapTap or Donkey Kong, where rhythmic structures are recognized and reproduced by non-musicians of all ages.

Rhythm in Cognitive Sciences

In physiology and neuropsychology, numerous studies report that humans have a natural perception of rhythm, thanks to rhythmic mechanisms that are involved in the internal functioning of our organism (heart beat, sleep cycles, etc.) [START_REF] Glass | Synchronization and rhythmic processes in physiology[END_REF] and their relation with periodic external phenomena (day/night, seasons, etc.). When listening to music, we constantly try to infer the beat, i.e., to perceive regular and salient events, or to group events into rhythms [START_REF] Large | Periodicity, pattern formation, and metric structure[END_REF]. In fact, we systematically try to perceive rhythm even when none is present [START_REF] Potter | Perceiving rhythm where none exists: Event-related potential (erp) correlates of subjective accenting[END_REF] or when being told to avoid it [START_REF] Fraisse | Rhythm and tempo[END_REF].

Rhythm perception is deeply related to the motor system [START_REF] Brochard | Evidence of beat perception via purely tactile stimulation[END_REF].

Since childhood, humans are used to tap their feet, clap their hands, snap their fingers and move in synchrony with music. These activities are common and seem simple, even though they involve complex rhythmic structures. Outside music, periodic activities of different frequencies are pervasive in our everyday life. For example, chewing or walking are known to have universally preferred rates [START_REF] Glass | Synchronization and rhythmic processes in physiology[END_REF][START_REF] Macdougall | Marching to the beat of the same drummer: the spontaneous tempo of human locomotion[END_REF].

While these studies attempt to explain how and why we perceive and produce periodicities, they rarely deal with the reproduction and memorization of rhythmic patterns associated to tasks that we address in this article.

Rhythm as an Input Method in HCI

Rhythm is built on the temporal dimension, which is commonly used in interactive software. For example, long clicks are often distinguished from short clicks to trigger different commands based on temporal criteria. The concept of "dwelling" -freezing the interaction for a short amount of time -is also used to segment gestural interaction [START_REF] Hinckley | Design and analysis of delimiters for selection-action pen gesture phrases in scriboli[END_REF] or to explicitly switch mode [START_REF] Faure | Power tools for copying and moving: useful stuff for your desktop[END_REF]. Rhythmic Menus [START_REF] Maury | Rhythmic menus: toward interaction based on rhythm[END_REF] successively highlight items at a given rate while the mouse button is pressed. When the user releases the button, the current item is selected.

Some techniques are based on the temporal grouping of events. Double click is the simplest and most common case, but some studies also explored rhythmic motion: Motion Pointing [START_REF] Fekete | Motion-pointing: target selection using elliptical motions[END_REF] assigns different periodic motions to graphical objects in a scene or items in a pie menu; The user selects the object or menu item of interest by performing the corresponding motion. In Cyclostar [START_REF] Malacria | Clutch-free panning and integrated pan-zoom control on touch-sensitive surfaces: the cyclostar approach[END_REF], the user controls continuous parameters, such as the speed of zooming, by performing elliptical oscillatory gestures. The rate of the circling motion controls a parameter of the resulting command.

In the above cases, rhythmic aspects are reduced to periodicity. To the best of our knowledge, only a few techniques involve the reproduction of rhythmic patterns. Five-key [START_REF] Szentgyorgyi | Five-key text input using rhythmic mappings[END_REF] is a text entry system based on rhythmic sequences, where letters can be entered with only five keys. However, efficiency and learning were not studied systematically. In [START_REF] Crossan | Rhythmic interaction for song filtering on a mobile device[END_REF], tempo reproduction is used to select a particular song in a music library by tapping on a mobile device or shaking it. But relying only on tempo raises some scalability issues that were not assessed. Finally, Tapsongs [START_REF] Wobbrock | Tapsongs: tapping rhythm-based passwords on a single binary sensor[END_REF] is an alternative to textual passwords where users tap a rhythmic pattern that they have registered with the system for authentication.

MOTIVATION

Our goals are more general than Five-key and Tapsongs: we want to design vocabularies of rhythmic patterns that users can learn easily and perform reliably in order to trigger commands. This approach is somewhat similar to the use of Morse code for encoding characters. However, the design of Morse code was driven by information theoretic issues rather than usability, and while early computers were able to decode human-produced Morse code [START_REF] Blair | On computer transcription of manual morse[END_REF], it has rarely been used in HCI [START_REF] Chen | A new assistive communication system for the serious disabled[END_REF]. Our objective is to propose a comprehensive framework to design rhythmic patterns for interaction, with efficient recognizers that do not need training.

Advantages of Using Rhythms for Input

The design of new techniques based on Rhythmic Interaction is not the main focus of the present article. However, we have identified a number of potential advantages of using rhythm to interact with computer systems. First, as evidenced by research in Cognitive Science, there is a direct correspondence between performing a rhythm (action) and listening to a rhythm (potential audio stimulus and feedback). Second, rhythms can be performed in a variety of situations: while performing a rhythm requires as little as a single degree of freedom of one finger, many movements can be performed rhythmically and captured using different sensors, e.g., tapping fingers, tapping feet, or nodding the head.

Gestural interaction typically requires space to perform the gestures, and often interferes with the display space on a small touchscreen. By contrast, Rhythmic Interaction only uses temporal features. Rhythms can be performed on a small area of a tactile device, even in an eye-free context.

Finally, rhythmic structures can be designed in a hierarchical way. By using common prefixes among different patterns, a natural hierarchy emerges that can be internalized by users, facilitating memorization and recall.

Applications of Rhythmic Patterns

Rhythmic patterns are not meant to replace more conventional command input methods. Instead, it is an alternative that may be more adapted to specific situations, such as eye-free operation. It is also a way to enhance existing methods with a richer vocabulary. For example rhythmic patterns could give access to a restricted set of commands such as speed-dialing a phone number, navigating an e-book or switching mode in an application.

In some situations, rhythmic patterns can simplify interaction. For example, bookmarks, menu items or contacts are often organized hierarchically. Rhythmic patterns could match this hierarchy or provide an alternate hierarchy such as organizing contacts by their first name. Also, since rhythmic patterns can be performed without visual attention, they can be used with a tactile device in the pocket or while driving, or in the dark, e.g. to shut down an alarm clock, or even with devices that do not have a display.

Rhythmic Interaction also offers novel solutions to wellknown problems. Tapping on the back of a hand-held device can be captured without extra sensors, thanks to built-in accelerometers or microphones [START_REF] Robinson | Tapback: towards richer mobile interfaces in impoverished contexts[END_REF]. For example, a rhythmic pattern performed while receiving a phone call could add the caller to the contact list, or display extra information such as battery life or signal level. Patterns could also be performed with the non-dominant hand or another part of the body such as the feet [START_REF] Scott | Sensing foot gestures from the pocket[END_REF], to switch mode or ignore an incoming call.

RHYTHMIC PATTERNS FOR INTERACTION

Our definition of a rhythmic pattern comes from music: The elementary structure in music is called a motif, which is defined as a "melodic, rhythmic, or harmonic cell" [START_REF] Manuel | Histoire de la Musique[END_REF].

A rhythmic motif represents the temporal structure of a set of notes and consists of the relative durations of notes and silences. Notes and silences can have eight different durations in standard musical pieces, and motifs can contain many notes, leading to a huge number of possible rhythmic motifs.

Considering the number of commands and actions often used when interacting with computers, such an expressive power is not required. Therefore we propose a restricted definition of rhythmic pattern (or simply pattern) more adapted to HCI. A rhythmic pattern is a sequence of taps 1 and breaks whose durations are counted in beats. The beat is the basic unit of time and its duration is defined below). We define the complete set of possible patterns with the following rules:

• Taps can be of three types: impulse (a hit on a touch device or a click), short tap (one beat) or long tap (two beats). A tap starts at the beginning of a beat, and there cannot be more than one tap per beat. • Breaks can be of two types: short (one beat) or long (two beats). A pattern cannot begin or end with a break, and there cannot be two successive breaks.

This definition of taps and breaks is based on our empirical observation that computer users are familiar with the distinction between instantaneous and long clicks or taps. By adding 1 The word "tap" reflects our focus on using a tactile device for input. a third duration and by taking breaks into account, we offer designers more possibilities for selecting a set of patterns among the possible combinations. In comparison to Morse code, we do not need the "intra-character", "inter-character" and "inter-word" breaks that are specific to the coding of language, and we do not allow more than one tap per beat.

The length of a pattern is the sum of the durations of its taps and breaks. To simplify reproduction and memorization, we focus on patterns between two and six beats long. The rules above define 5 two-beat patterns, 16 three-beat patterns (Figure 1), 53 four-beat patterns, 171 six-beat patterns and 554 six-beat patterns. By comparison, the total number of patterns with n taps is 3 2n-1 , i.e. 199, 290 patterns with up to six taps.

In this entire study, beats occur at the tempo of 120 BPM (2Hz). Thus, the onsets of two consecutive taps are separated by at least 500 ms, i.e. a beat is half a second. This corresponds to a common tempo of human motor actions, e.g. walking [START_REF] Macdougall | Marching to the beat of the same drummer: the spontaneous tempo of human locomotion[END_REF], and of contemporary music [START_REF] Moelants | Preferred tempo reconsidered[END_REF].

As a first step, we only consider rhythmic patterns performed by tapping on a touch-sensitive surface. While keyboards, accelerometers [START_REF] Lantz | Rhythmic interaction with a mobile device[END_REF][START_REF] Crossan | Rhythmic interaction for song filtering on a mobile device[END_REF] or eye blinks [START_REF] Westeyn | Recognizing song-based blink patterns: Applications for restricted and universal access[END_REF] can probably be used for Rhythmic Interaction, it is out of the scope of this article. We also do not address the segmentation of patterns from other input. Simple solutions that should be tested include segmenting in time by preceding each pattern with a specific short sequence of taps, or segmenting in space by performing patterns on a specific location of a device.

A key aspect of this research is to design a recognizer that can reliably identify the patterns produced by users. In a first experiment, we used a structural recognizer to assess users' ability to produce patterns accurately. Based on the results, we designed a pattern classifier that accounts for user inaccuracies while still discriminating the patterns in the vocabulary. This classifier was used in a second experiment where we assessed users' ability to memorize associations between patterns and commands in an applicative context.

EXPERIMENT 1: RHYTHMIC PATTERN REPRODUCTION

In order to assess the potential of Rhythmic Interaction, we conducted a first experiment where novice users were asked to replicate patterns presented to them in visual and/or audio form by tapping on a touch surface. The goal was to assess the accuracy of the reproduction and to compare the effects of several feedback mechanisms while performing patterns.

Recognizer

The recognizer that we designed for this experiment is based on the above rules for defining the patterns. It first extracts the rhythmic structure as a list of taps and breaks and infers their respective types (impulse, short and long) using autonomous heuristics. The reconstructed pattern is then checked against the vocabulary used for the study.

In order to identify the type of every tap and break in the sequence, the recognition algorithm uses k-means clustering iterated 500 times on duration values. The algorithm builds clusters corresponding to the possible types of taps and breaks: impulse, short and long2 . A minimum distance of 200ms between the duration clusters is enforced, corresponding to a maximum tempo for the pattern to be recognized. If two clusters are closer than that distance, they are merged and will be recognized as a single tap type. Thus, if the pattern is performed too fast, events of different types may be confused by the recognizer. For cluster identification, the reference durations for short and long taps or breaks are set to 500ms and 1000ms respectively, and the maximum duration of an impulse or release is set to 180ms.

After clustering, breaks that correspond to the rest of a beat after an impulse are removed from the reconstructed pattern. The resulting pattern is then looked up in the vocabulary to check if it matches the stimulus provided to the participant.

Note that this recognizer is intentionally very strict, in order to assess the participants' ability to precisely reproduce the patterns. In particular, if the reconstructed pattern is not in the vocabulary, the recognizer will systematically return an error.

With minimal knowledge about our definition of rhythmic patterns, the algorithm is able to identify the type of every tap and break in a sequence even in tricky situations, such as when there is just one type of events. Thanks to clustering, the recognizer adapts to the tempo (the overall tempo can be inferred by comparing the centroids of the clusters.)

Apparatus and Participants

The experiment was implemented in Java and conducted on a 13" Apple MacBook (Intel processor). Participants tapped the rhythmic patterns on the embedded multitouch trackpad.

Twelve unpaid volunteers (six female) participated in this experiment, with age ranging from 23 to 53 (mean 29, median 27). Five of them had never practiced music.

Stimulus

The pattern to reproduce is presented to the participant with a stimulus combining a static graphical representation of the pattern, visual animation and audio (Figure 2). The visual stimulus is a stationary shape depicting the whole rhythmic pattern, where each rectangle represents an event (Figure 2a). This shape is then progressively filled (Figure 2b) in synchrony with audio playback. Beats are marked with thin gray lines to visualize the durations of events.

For audio playback and animation, impulses last 125ms and the tempo is set to 120 BPM or 2Hz (500ms period). This value is above the "synchronization threshold" [START_REF] Repp | Rate limits in sensorimotor synchronization[END_REF] for both visual and auditive stimulus, ensuring that participants can perceive and perform it accurately. The audio stimulus is a 440Hz A, played by the General MIDI Instrument "English Horn" and held at a constant sound level. We chose this sound as it is soft enough for the subjects to endure during the experiment, but has clear onset and release.

Feedback

Participants are presented with 4 input FEEDBACK conditions while reproducing rhythmic patterns. The Audio feedback plays the same sound as the stimulus as long as the participant is touching the surface of the trackpad. The V isual feedback is based on the graphical representation of the stimulus.

The rectangles representing the events appear dynamically while the subject is tapping on the trackpad (Figure 3). The AudioV isual feedback combines the two previous methods, and there is no feedback at all in the N one condition.

The Audio, V isual and AudioV isual feedback methods are expected to help learning, e.g. in novice mode. Conversely, the N one condition corresponds to the situation where an expert user is performing patterns in an eyes-free manner without audio feedback.

Vocabulary

For this experiment, we selected 30 rhythmic patterns among the 799 patterns with two to six beats generated by the rules described earlier. This vocabulary (Figure 4) contains 4 twobeats patterns, 8 three-beats patterns, 8 four-beats patterns, 6 five-beats patterns and 4 six-beats patterns. We explicitly featured fewer patterns for the extreme situations (two, five and six beats). Among the patterns with the same duration, we tried to balance the number of events. For example, for the 8 four-beat patterns, 2 contain two events, 3 contain three events and 3 contain four events.

Task

A trial consists in reproducing a rhythmic pattern according to the FEEDBACK condition, right after it is presented twice in a row. The participant performs the pattern by tapping on the trackpad with the index finger of her dominant hand. The recognizer then computes the temporal structure of the input and matches it with that of the stimulus. At the end of the trial, the participant is notified about the success or the failure of the match before advancing to the next trial.

Design and Procedure

The experiment is a 2×30 within-subject design with factors: (i) FEEDBACK: Audio, V isual, AudioV isual and N one; and (ii) PATTERN: P1 -P30 (Figure 4).

At the beginning of the session, each FEEDBACK condition is introduced to the participant with a short block of 15 random trials. Then, the participant is asked to perform two warm-up blocks of 15 trials in the AudioV isual feedback condition, which we hypothesize provides the best feedback to become familiar with the task. The 3 first trials of the first warm-up block are performed by the experimenter to demonstrate the feedback condition to the participant. The second warm-up block is interrupted if the participant reports to be confident enough to start the experiment.

During the main session, measured trials are grouped into blocks according to the FEEDBACK factor. The presentation order for FEEDBACK is counterbalanced across participants with a Latin square. Within each block, the 30 patterns are repeated twice in randomized order. A practice block of 15 randomly selected patterns is performed prior each measured block and participants are allowed to have breaks between and in the middle of each block. Thus, we collected 12 participants × 4 FEEDBACK × 30 PATTERN × 2 repetitions = 2880 measured trials. Participants were instructed to be as accurate as possible by paying attention to the discrimination of different types of taps and breaks. Each participant took about one hour to complete the sessions, after which they were asked to rank the feedback methods according to the difficulty of the task on a 5-point Likert's scale.

Quantitative Results

The overall success rate is 64.3%. This may seem low, but recall that our recognizer is deliberately very strict regarding the temporal structure of patterns, and that it can recognize all 799 patterns with two to six beats, not just the 30 patterns in the study. The precise reproduction of the rhythmic patterns in the study is similar to playing a percussion instrument, a task that musicians can take years to master. Figure 5 shows typical reproduction errors by study participants, such as release breaks that are too long and recognized as short breaks, or breaks or taps that are too similar to be separated during clustering. Interestingly, errors seem more frequent with breaks than with taps, which is consistent with the finding that users tend to be more precise when performing notes than pauses [START_REF] Rammsayer | Duration discrimination of filled and empty auditory intervals: Cognitive and perceptual factors[END_REF].

A one-way ANOVA for FEEDBACK (with participant as a random variable) reveals a significant effect on success rate (F 3,33 = 15.4, p < 0.0001). This effect can be observed in Figure 6 3 . Post-hoc t-tests with Bonferroni correction show that the N one condition is significantly worse than all other feedback conditions. It is not surprising that the absence of feedback while performing the pattern significantly degrades the accuracy of rhythm reproduction. Regarding PATTERN, a one-way ANOVA reveals a significant effect on success rate (F 29,319 = 25.1, p < 0.0001). We observe a large deviation of the success rate for some patterns: from 16% with P27 to 98% for P10. Fifteen patterns have a success rate of at least 70%: P1-P7, P9-P13, P19, P20, and P29. All have at least 3 taps and all but P29 are less than four-beats long. However, some three-tap patterns have a low success rate (below 50%): P14 and P18 (both with 4 beats).

We could not identify similarities among the patterns that were difficult to reproduce. However, the number of taps and beats are the most obvious characteristics that can influence the ease of reproduction. In fact, we found a significant effect on success rate for taps (F 4,44 = 54.1, p < 0.0001) and beats (F 4,44 = 85.5, p < 0.0001), without significant interaction with FEEDBACK. Post-hoc t-tests support this hypothesis since, in most cases, the highest recognition rates were achieved for patterns with a small number of taps or beats (Figure 7).

Qualitative Results

Six participants out of 12 preferred the Audio feedback, 3 the V isual feedback, 2 the AudioV isual feedbacks and 1 no feedback. Moreover, 6 participants ranked AudioV isual second and 8 ranked the N one condition last. Note that many participants pointed out that AudioV isual was confusing, providing too much information. They explained that in most cases, they chose one feedback (visual or auditive) and tried to ignore the other. Half of them preferred the Audio feedback because it was more related to rhythm than graphics.

We assessed the subjective difficulty of the task with the statement "I found it difficult to reproduce rhythmic patterns". Seven participants disagreed or strongly disagreed, 4 neither disagreed nor agreed, and only one agreed, but at the same time disagreeing for the N one and V isual feedbacks.

Overall, both quantitative and qualitative results are encouraging and support our hypothesis that rhythmic patterns, as defined by our framework, is a viable input technique for interactive tasks. While quantitative results support the need to provide feedback while performing input, qualitative results inform on the type of appropriate feedback. Finally, an analysis of recognition errors gives insights on how to create a recognizer that would be more suitable for real applications.

A PATTERN CLASSIFIER

The goal of the structural recognizer in Experiment 1 was to assess how accurately participants could reproduce a stimulus pattern. This recognizer is deliberately strict, accounting only for variations in the overall tempo of the pattern, and it does not take advantage of the fact that the input patterns are assumed to be part of a known vocabulary. We designed a second recognizer for use in actual applications, that classifies an input pattern against a vocabulary.

In order to recognize a sequence of taps, this pattern classifier first counts the number of taps in the sequence and considers the subset of the vocabulary with that number of taps. Then, it calculates a score for each candidate pattern. First, it infers the duration of a beat by considering the duration of the sequence of taps and the number of taps of the candidate.

Using this value, it scales the pattern to match the duration of the input sequence and sums the temporal differences of events onsets and durations. A duration of a quarter beat is used for impulses and releases between consecutive events (when lifting the finger from the device). Finally, the score is weighted by the ratio between the inferred beat duration and the 120 BPM reference (500ms).

This classifier is less strict than the structural recognizer because it will always match an input pattern to a pattern in the vocabulary if it is the only one with the same number of taps, unless a threshold is set on the lowest acceptable score. Moreover, normalization makes the recognizer match patterns that are homothetic of each other. This is the reason for weighing the score by the relative beat durations.

We tested this classifier with the data and vocabulary of Experiment 1. The overall success rate rose to 93.9%, more in line with the expectations of an applicative context. As with the previous recognizer, a one-way ANOVA for FEEDBACK reveals a significant effect on success rate (F 3,33 = 7.2, p = 0.0007) (Figure 8).

Figure 9 shows that unlike the structural recognizer, success rate does not decrease with pattern "complexity": there is no significant effect of the number of taps or the length on success rate 4 . Instead, we observe that success rates are affected by the similarity between patterns: a complex pattern can be recognized quite reliably provided that it is sufficiently different from other patterns with the same number of taps. For example, P30 is the only pattern made of 6 taps in our set, making recognition failure occur only when the subject tapped a wrong number of taps. By contrast, P17 seems to be more "complex" than the "simple" pattern P20 but the former has a 100% success rate and the latter 82%. In fact, the recognizer sometimes confuses P20 with P11. However, a post-hoc t-test with Holm correction reveals no significant difference between patterns for success rates.

In summary, we found that this classifier was well adapted to actual applications. In particular, a designer can create a vocabulary that minimizes the risk of patterns being confused.

EXPERIMENT 2: RHYTHMIC PATTERNS MEMORIZATION

In order to further validate Rhythmic Interaction, we conducted a second experiment to test whether patterns can be memorized and recalled in order to be used as an alternative to standard techniques for triggering commands. We compared rhythmic patterns with standard hotkeys in a "learn and recall" experiment similar to Appert and Zhai's comparison of gesture shortcuts with hotkeys [START_REF] Appert | Using strokes as command shortcuts: cognitive benefits and toolkit support[END_REF], itself inspired by Grossman et al's study of hotkeys [START_REF] Grossman | Strategies for accelerating on-line learning of hotkeys[END_REF].

Variables

We compare two techniques for triggering commands (TECH factor): Hotkey and Rhythm. A third condition, F ree, lets participants choose the technique they prefer.

Each command C i is a triplet associating an image I i , used as a stimulus for this command, and two triggering techniques: a rhythmic pattern R i and a hotkey K i . The command set (CMD factor) has 14 commands: C 1 , ..., C 14 . We chose the images symbolizing the commands in a set of common objects and fruits (Figure 10).

For the rhythmic patterns, we selected 14 patterns of varying complexity from Experiment 1 and randomly assigned each pattern to a command. For the hotkeys, we created combinations of a modifier (Shift or Ctrl) and a letter. The letters were chosen so that they did not match the first letter of the name of the object representing the command, as in [START_REF] Appert | Using strokes as command shortcuts: cognitive benefits and toolkit support[END_REF]. The goal is to avoid giving an unfair advantage to hotkeys, since there is no similar mnemonic association between rhythmic patterns and command names. Furthermore, the mapping between commands and hotkeys often varies by application and language. Figure 10 shows the resulting assignment.

Task

The primary task of the experiment is to activate a command (C i ), presented by its stimulus image (I i ), with the triggering technique corresponding to the current TECH condition (R i or K i ). The experiment has two phases: learning and testing.

During the learning phase, both the image I i and the corresponding triggering technique (R i or K i ) are shown to the participant. For rhythmic patterns, the static graphical representation is displayed next to the image (Figure 11a) and the audio stimulus is played twice. Hotkeys are presented with a short animation of the corresponding key-press sequence, also repeated twice, and text (Figure 11b).

In the testing phase, participants are presented with the image I i only (Figure 11b). According to the current TECH condition, they must perform the corresponding hotkey K i or rhythmic pattern R i . If they forgot which trigger to perform, they are strongly encouraged to invoke a help screen by pressing the SP A C E key. The task then switches to the learning mode, presenting the shortcut to perform as described above.

In both phases, the participant must perform the rhythmic pattern or the hotkey. For rhythmic patterns, we use the Audioonly feedback since Experiment 1 showed that it was effective and participants preferred it. Also, this avoids interference with the visual interface. For hotkeys, participants receive the usual kinesthetic feedback while pressing keys.

After entering each hotkey or pattern, the participants are asked to indicate which trigger they were trying to perform (Figure 12). Then, participants are notified of the correctness of their answer. If the answer is correct, they are given the result of the recognition. If not, the correct trigger is presented before moving to the next trial. The reason for this procedure is that we are primarily interested in the memorization of the associations, not the participants' ability to perform the triggers. For rhythmic patterns, it also allows us to test the recognition rate of the classifier.

Apparatus & Participants

We used the same apparatus as in Experiment 1. We recruited 14 participants (5 female), aged between 22 and 33 (mean 26, median 26). Five of them had participated in Experiment 1.

Design & Procedure

The experiment is a within-subject design with technique (TECH) and command (CMD) as primary factors. The experiment is split into two sessions held on two consecutive days. The first day, all participants are presented with rhythmic patterns in a 5 minutes practice session based on Experiment 1. We use TECH as a blocking factor, counterbalanced across participants. The second day, a F ree block is added at the end of the testing phase. In this block, participants can choose to use Rhythm or Hotkey for each trial, but cannot get help.

Each TECH-block is divided into several sub-blocks of 15 trials: (i) 2 learning sub-blocks with 4 testing sub-blocks each on the first day; (ii) 4 testing sub-blocks on the second day. Thus, the testing phase of the experiment is split into SUBSESSIONs of 60 trials each: two on the first day to evaluate immediate memorization of triggering commands and one on the second day to test mid-term recall (Figure 13).

In order to simulate a more realistic setup, where some commands are more frequently used than others, we assign an apparition frequency to each of the 14 commands following a Zipf distribution [START_REF] Grossman | Strategies for accelerating on-line learning of hotkeys[END_REF][START_REF] Appert | Using strokes as command shortcuts: cognitive benefits and toolkit support[END_REF]. For the learning phase we use the frequencies (6, 6, 3, 3, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1) and for the testing phase [START_REF] Fraisse | Rhythm and tempo[END_REF][START_REF] Fraisse | Rhythm and tempo[END_REF][START_REF] Chen | A new assistive communication system for the serious disabled[END_REF][START_REF] Chen | A new assistive communication system for the serious disabled[END_REF][START_REF] Blair | On computer transcription of manual morse[END_REF], 4, 3, 3, 2, 2, 2, 2, 1, 1). The 14 commands are combined with these frequencies using 7 different permutations, and each frequency assignment is counterbalanced across participants, resulting in the same number of trials for each command overall. The presentation of the trials is randomized across consecutive pairs of subblocks.

The experiment takes about one hour on day 1 and 30 minutes on day 2, after which participants are given a questionnaire to collect subjective observations and preferences.

Quantitative Results

Our main measures are (i) recall rate, the percentage of correct answers in the testing phase without help; and (ii) help rate, the percentage of trials where the participants used help in the testing phase. We analyze the results according to TECH and the three sub-sessions of the experiment by considering these measures in the model TECH × SUBSESSION × Rand(PARTICIPANT).

We find a significant effect of SUBSESSION on the recall rate (F 2,26 = 103, p < 0.0001). A post-hoc t-test with Bonferroni correction shows that the recall rate is significantly lower only between the first sub-session and the two following ones (Figure 14). There is no significant effect of TECH on recall rate (F 1,13 = 0.61, p = 0.4474), but the ANOVA reveals a significant interaction effect TECH × SUBSESSION (F 2,26 = 5.36, p = 0.0113). Post-hoc t-tests with Bonferroni correction show a significant difference between Rhythm and Hotkey for the first sub-session (74% and 81% respectively). For the remaining sub-sessions, the results are extremely close between the two techniques with a recall rate of about 93% (Figure 14).

For the use of help, an ANOVA reveals a significant effect of SUBSESSION (F 2,26 = 17.3, p < 0.0001), no effect of TECH (F 1,13 = 0.04, p = 0.8532), and no TECH × SUBSESSION interaction effect (F 2,26 = 0.62, p = 0.545). We find only one significant difference among sub-sessions: help was used more often in the first sub-session than in the two subsequent ones (see Figure 15). Results for rhythmic patterns and hotkeys are quite similar, suggesting that rhythmic patterns can be memorized as successfully as hotkeys without mnemonics. This is a remarkable result considering how widespread hotkeys are.

Recall rates are consistent across commands. Considering only the Rhythm condition, we build the model CMD × SUBSESSION × Rand(PARTICIPANT) for recall rate and help and see a significant effect of CMD on recall rate (F 13,169 = 1.17, p = 0.025). A post-hoc t-test with Holm corrections shows significant differences only between R 3 and R 13 (recall rate about 97%) and R 10 , R 11 and R 14 (∼80%).

To test our classifier, we compare the pattern recognized by the classifier with the answer selected by the participant using the model TECH × SUBSESSION × Rand(PARTICIPANT). We find a significant effect of TECH (F 1,13 = 5.34, p = 0.038), with Rhythm having a significant lower success rate than Hotkey: 85.2% vs. 91.8%. The success rate for Hotkey is surprisingly low, as we expect few if any errors when entering hotkeys. This may be due to participants changing their mind as to which was the right hotkey when they see the answer sheet. For Rhythm, the rate is also lower than expected, but the same phenomenon may have occurred. Indeed, the success rate of Rhythm relatively to Hotkey is 92.8%, close to the rate obtained on the data for Experiment 1 (94%).

Qualitative Results

Figure 16 shows the percentage of trials where participants used rhythmic patterns in the F ree condition, on the second day of the experiment. Ten participants (out of 14) used rhythmic patterns more often than hotkeys. Seven participants used rhythmic patterns more than 80% of the time, while only one participant used rhythmic patterns less than 20% of the time.

The answers to the questionnaire were generally positive, confirming the previous results. Out of the 14 participants, 9 preferred using the rhythmic patterns, 3 the hotkeys, 2 had no preference. Those who preferred using rhythmic patterns did so mostly because of the "fun factor" of tapping rhythms, but also because it could be performed "in place" on the trackpad, even for a novice user, without having to visually search the keys on the keyboard. On the other hand, several participants noticed that hotkeys are faster to perform and preferred to use hotkeys when the corresponding pattern is too long.

Regarding memorization, some participants reported using mnemonics related to the rhythm itself in order to help memorization. For instance, a subject linked the "boxing gloves" command and the corresponding pattern P9 (Figure 4) to a "pif paf boom" onomatopoeia that, for him, echoed the "short short medium" structure of the pattern. Another participant also reported linking the pattern structure with the pronunciation of the object's name, e.g., "toma-to-to-to-to" for command 13 and pattern P28. Subjects also used the graphical representation of patterns to memorize them, which supports our design for this representation. For example, one participant stated that "the rhythmic pattern's visual representation for the cherry looks like a cherry". These comments suggest that users elaborate efficient strategies for the memorization of rhythmic patterns, based on the rhythm itself or its visualization. Since commands were assigned to rhythmic patterns randomly, we did not expect such associations, but this finding opens the way to studying ways to reinforce these associations. This is commonly done for gestures, e.g., a question mark for help, and hotkeys, e.g. Ctrl-S for Save. In particular, various strategies could be explored to create visual "cheatsheets" for rhythmic patterns or display them next to menu commands, like hotkeys.

In addition, the complexity of performing rhythmic patterns can be turned into an advantage for memorization. Since deeper and greater numbers of levels of encoding and processing help memory [START_REF] Craik | Levels of processing: A framework for memory research[END_REF], combining motor and auditive perception of rhythmic patterns may help users memorize, i.e., encode, their associations with commands.

SUMMARY AND PERSPECTIVES

In this paper we studied the use of rhythmic patterns in HCI. We explored Rhythmic Interaction as an opportunity to generalize the primitive use of rhythm in existing techniques, e.g., long click and double click, as well as to promote a new input modality. Since Rhythmic Interaction relies on the time dimension instead of the spatial and visual dimensions used by most input methods, it is well suited when space is limited or when visual attention is not available.

We presented a grammar for creating rhythmic patterns as well as two recognizers that do not require training. A first experiment evaluated the ability of casual users to reproduce rhythmic patterns very precisely with different feedback conditions. We found that some complex patterns can be difficult to reproduce in such a precise way, but that audio and/or visual feedback improve accuracy. After analyzing recognition errors, we designed a different recognizer that reached 94% recognition rate for the 30-pattern vocabulary of Experiment 1. We ran a second experiment to investigate the memorization of associations between rhythmic patterns and commands, i.e., rhythmic shortcuts. The results suggest that rhythmic patterns are recalled as efficiently as traditional hotkeys and that users create effective mnemonic strategies to associate rhythms with commands. This work demonstrates the potential of rhythmic patterns as an input method, and contributes a 14-pattern vocabulary that has proven usable by novice users. Beyond triggering commands and switching modes in standard desktop environments, rhythmic patterns could be used in many contexts: eye-free control of a mobile device, such as a cellular phone or a mobile player; remote control of interactive environments such as wall-size displays by tapping on wearable sensors without the need for visual attention; selection of an object on a tabletop when it is not easily reachable, etc.

Our future work will address issues such as the segmentation of patterns, the scalability of the vocabularies and the speed of execution, which are important for the design of Rhythmic Interactions. Another area for future work is the use of multiple fingers or both hands to tap patterns and to combine rhythmic interaction with other interaction techniques. More complex actions than tapping should also be explored to enter rhythmic structures, such as performing sequences of gestures or keyboard taps, as well as the use of the temporal dimension to convey additional information. Furthermore, rhythmic output, such as vibration patterns on mobile devices, seems worth studying since perception and performance of rhythmic patterns are tightly linked. Finally, the power of rhythmic interaction could be expanded by exploiting syntactic features used in music such as performing sequential or parallel combinations of patterns.

E

  . Ghomi, G. Faure, S. Huot, 0. Chapuis, and M. Beaudouin-Lafon. Using Rhythmic Patterns as an Input Method. In CHI '12: Proceedings of the SIGCHI Conference on Human Factors and Computing Systems, 1253-1262, ACM, 2012. http://doi.acm.org/10.1145/2207676.2208579 c ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version will be published in CHI'12, May 5-10, 2012, Austin, Texas, USA.

Figure 1 .

 1 Figure 1. The 16 three-beat patterns defined by our rules. Each rectangle represents a tap. The thin gray lines show the beats.

Figure 2 .

 2 Figure 2. The stimulus in Experiment 1. A static representation is displayed (a) and fills up in synchrony with the audio playback (b).

Figure 3 .

 3 Figure 3. Visual feedback while tapping a pattern.

Figure 4 .

 4 Figure 4. Vocabulary used in the first experiment.

Figure 5 .Figure 6 .

 56 Figure 5. Two stimuli (P21 and P27) with reproductions errors by subjects of Experiment 1. S4: the last break is too long (a); S5: the last tap is too long (b); S1: the last break is too short S3: the first break is too long (d), the last break is too short (e).

Figure 7 .

 7 Figure 7. Success rate by number of taps and by length in beats.

Figure 8 .Figure 9 .

 89 Figure 8. Revised success rate by FEEDBACK for the pattern classifier.

Figure 10 .

 10 Figure 10. Commands used in Experiment 2. Pxx refers to the patterns of Experiment 1 (see Figure4).

11 .

 11 Stimulus in the learning phase for the Rhythm (a) and Hotkey (b) conditions, and in the testing phase for both conditions (c).

Figure 12 .Figure 13 .

 1213 Figure 12. Confirmation in the Rhythm (a) and Hotkey (b) conditions. Feedback for a wrong answer in the Rhythm condition (c)).

Figure 14 .Figure 15 .

 1415 Figure 14. Recall rate for both techniques by sub-session.

Figure 16 .

 16 Figure 16. Percentage use of Rhythm by participant (F ree condition).

A break with a duration of an impulse is called a release. It occurs between two adjacent taps.

In all figures, error bars show the 95% confidence interval.

This could be due to the fact that in the vocabulary, there were few patterns with five taps or beats.

ACKNOWLEDGEMENTS

We thank Caroline Appert for feedback on earlier versions of this paper, our participants and the anonymous reviewers.


Professor J-M M Regimbeau
email: regimbeau.jean-marc@chu-amiens.fr

MD D Fuks

MD P Bachellier

MD Y P Le Treut

MD, PhD F R Pruvot

MD F Navarro

MD L Chiche

MD, PhD O Farges

Prognostic value of jaundice in patients with gallbladder cancer by the AFC-GBC-2009 study group

Keywords: Gallbladder carcinoma, PVE: Portal vein embolization, PD Gallbladder carcinoma, Jaundice, Extended Liver resection, Morbidity, Mortality, Long-term survival

Introduction. Jaundice is frequent in patients with gallbladder cancer (GBC) and indicates advanced disease and, according to some teams, precludes routine operative exploration. The present study was designed to re-assess the prognostic value of jaundice in patients with GBC.

Methods. Patients with GBC operated from 1998 to 2008 were included in a retrospective multicenter study (AFC). The main outcome measured was the prognostic value of jaundice in patients with GBC focusing on morbidity, mortality and survival.

Results. 110 of 429 patients with GBC presented with jaundice, with a median age of 66 years (range: 31 -88). The resectability rate was 45% (n=50) and the postoperative mortality and morbidity rates were 16% and 62%, respectively; 71% had R0 resection and 46% had lymph node involvement. Overall 1-and 3-year survivals of the 110 jaundiced patients were 41% and 15%, respectively. For the 50 resected patients, 1-and 3-year survivals were 48% and 19%, respectively (real 5-year survivors n=4) which were significantly higher than that of the 60 non-resected patients (31%, 0%, p=.001).

Among the resected jaundiced patients, T-stage, N and M status were found to have a significant impact on survival. R0 resection did not increase the overall survival in all resected patients, but R0 increased median survival in the subgroup of N0 patients (20 months versus 6 months, p=.01).

Conclusion.

This series confirms that jaundice is a poor prognostic factor. However, the presence of jaundice does not preclude resection, especially in highly selected patients (N0).

INTRODUCTION

Most patients with gallbladder cancer (GBC) still present with advanced tumors [START_REF] Donohue | Present status of the diagnosis and treatment of gallbladder carcinoma[END_REF]. The only curative treatment remains resection [START_REF] Fong | Gallbladder cancer: comparison of patients presenting initially for definitive operation with those presenting after prior noncurative intervention[END_REF]. Jaundice occurs in up to 30 to 50% of patients with GBC [START_REF] Hawkins | Jaundice predicts advanced disease and early mortality in patients with gallbladder cancer[END_REF][START_REF] Regimbeau | Chirurgie des cholangiocarcinomes intrahépatiques, hilaires et vésiculaires[END_REF]. Although obstructive jaundice can sometimes be due to concomitant common bile duct stones [START_REF] Redaelli | High coincidence of Mirizzi syndrome and gallbladder carcinoma[END_REF], tumor thrombus [START_REF] Rau | Gallbladder cancer revealed by a jaundice caused by an endobiliary tumor thrombus[END_REF], or obstruction caused by lymph node involvement, jaundice mostly implies tumor extension to the common bile duct and biliary confluence [START_REF] Shimizu | Should the extrahepatic bile duct be resected for locally advanced gallbladder cancer?[END_REF].

The first series focusing on jaundice in patients with GBC was based on 82 patients [START_REF] Hawkins | Jaundice predicts advanced disease and early mortality in patients with gallbladder cancer[END_REF].

In this study, only 6 patients were resected with curative intent, and only 4 had negative surgical margins. Their median disease-specific survival was 6 months. In the light of these results, the authors concluded that "These data do not support routine operative exploration of patients with jaundice secondary to gallbladder cancer". However, several series experienced teams did not report such a poor outcome and showed that some jaundiced patients obtained improved survival following resection of GBC [START_REF] Kondo | Factors influencing postoperative hospital mortality and long-term survival after radical resection for stage IV gallbladder carcinoma[END_REF][START_REF] Miyazaki | Radical surgery for advanced gallbladder carcinoma[END_REF][START_REF] Todoroki | Outcomes of aggressive treatment of stage IV gallbladder cancer and predictors of survival[END_REF][START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF][START_REF] Varma | Does the presence of jaundice and/or a lump in a patient with gall bladder cancer mean that the lesion is not resectable?[END_REF]. A subgroup of jaundiced patients may therefore benefit from resection.

This study was designed to re-assess the prognostic value of jaundice on short and longterm outcome of patients undergoing radical surgery for GBC.

METHODS

Source and selection of patients

The AFC-GBC-2009 study group, composed of tertiary centers, was created in 2009 under the auspices of the French Association of Surgery (AFC) to produce a retrospective registry of operated GCB patients. Twenty-one centers were asked to: 1/ identify all patients operated for GBC between 1998 and 2008, 2/ fill in a multi-item questionnaire, 3/ return these questionnaires by June 2009. The protocol was approved Patients with Klatskin tumors or intrahepatic cholangiocarcinoma were excluded from the analysis.

Data review

If the information could not be retrieved from the medical files, a "not found / not performed" box was available. Coded data were repeatedly checked at random and some pathological data were used as controls. Centers were contacted again when: 1/ some items of the questionnaire had not been answered, 2/ discordant information was present in the questionnaire or between the questionnaire and the pathology report or 3/ last follow-up was less than 6 months.

Criteria studied

Criteria studied were presented in Table 1. R0 or R1 resections were considered to be curative resections. According to the UICC / AJCC TNM (7 th edition 2010) (13), regional lymph nodes (gallbladder, pericholedochal, hepatic pedicle, proper hepatic artery and periportal nodes) were considered to be N1. Involvement of the celiac trunk, superior mesenteric artery and para-aortic lymph nodes was classified as M1 disease. Routine sampling of inter-aortocaval lymph nodes was not performed in this study.

Postoperative hepatic insufficiency was defined by elevation of serum total bilirubin

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6 level > 2.9 mg/dL and prothrombin time < 50% persisting for more than 5 postoperative days [START_REF] Paugam-Burtz | Prospective validation of the "fifty-fifty" criteria as an early and accurate predictor of death after liver resection in intensive care unit patients[END_REF][START_REF] Balzan | The "50-50 criteria" on postoperative day 5: an accurate predictor of liver failure and death after hepatectomy[END_REF].

Statistical analysis

Non-parametric data are presented as median (range) and categorical data are presented as frequency and proportion (%). Categorical data were analyzed using Pearson's chi-square test and the Mann-Whitney U test was used for data not following a normal distribution. Subsequently, Kaplan-Meier survival curves were plotted and log-rank statistics were calculated to assess which variables affected survival time.

Significance levels were set at p<.05. All statistical tests were performed using SPSS software (version 15.0 for Windows, SPSS Inc., Chicago, IL, USA).

RESULTS

Demographic data

Of the 429 patients managed for GBC during this ten-year inclusion period, 110 were jaundiced, corresponding to 43 men and 67 women with a median age of 66 years (range: 31 -88). No significant difference was observed between jaundiced and nonjaundiced patients in terms of risk factors and co-morbidities (Table 1).

Preoperative management

At the end of preoperative staging, the rate of suspicion of arterial (6 vs. 1%, p = .008), portal vein (12 vs. 2%, p=.0001) and adjacent organ invasion (8 vs. 3%, p=.02) on preoperative imaging was significantly higher in jaundiced patients than in nonjaundiced patients.

Histologic evidence of cancer was obtained in 23 jaundiced patients planned for curativeintent resection.

Laparoscopic assessment was performed in 14 jaundiced patients and revealed a

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contraindication to resection in 8 patients consisting in peritoneal carcinomatosis (n=2), liver metastases (n=2), positive lymph node involvement (site of lymph nodes not specified) (n=2), malignant infiltration of the hepatoduodenal ligament (n=1) and vascular involvement (n=1). Among 319 non-jaundiced patients, laparoscopic assessment was performed in 24 patients and revealed a contraindication to resection in 6 patients (p<.04).

The median preoperative serum bilirubin level among jaundiced patients was 10.6mg/dl (range: 5.2-38.3). Forty-nine jaundiced patients underwent preoperative biliary drainage (endoscopically 67%). Drainage-related cholangitis was observed in 6 cases. Seven patients underwent right portal vein embolization (PVE) before scheduled extended right hepatectomy.

Seven patients received neoadjuvant chemotherapy (always gemcitabine-based) and/or radiation therapy and 1 patient received both of these treatment modalities.

Surgical procedures

A contraindication to resection was discovered in 52 out of 96 patients undergoing laparotomy (Figure 1). Contraindications in the 60 non-resected jaundiced patients (52 after laparotomy and 8 after laparoscopic assessment) were extensive infiltration of the hepatoduodenal ligament (n=16), peritoneal carcinomatosis (n=11), liver metastasis (n=8), positive lymph node (site of lymph node not specified) (n=8), vascular involvement (n=2), presence of cirrhosis (n=2) and involvement of adjacent organs (n=4). The reason for unresectability was not specified in the questionnaire for 9 patients.

Fifty jaundiced patients underwent curative resection including liver resection in every case (Table 1). A major hepatectomy (≥ 3 segments) was performed in 23 patients including excision of segment I in 6 patients. A lymphadenectomy was associated in 41

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patients, including the hepatoduodenal ligament in all cases, the celiac trunk in 8 cases and the para-aortic area in 3 cases patients. Forty-one jaundiced patients underwent common bile duct resection, and for the other 9 patients, frozen section did not reveal any tumor involvement of the cystic duct. Median operating time was 360 min (range: 90-680) and 23 patients received intra-operative transfusion. The portal vein was resected in 9 patients (of the 13 patients with suspected preoperative portal vein involvement) and one patient had inferior vena cava patch resection. Fourteen jaundiced patients (underwent resection of adjacent organs including 5 pancreaticoduodenectomies (PD) (Table 1). Resectability was significantly lower in jaundiced patients than in non-jaundiced patients (45% vs. 65%, p=.001). Jaundiced patients had significantly more major hepatectomies (56 vs. 17%, p=.0001), more portal vein resections (18 vs. 0.5%, p=.0001), more common bile duct resections (82 vs. 34%, p=.0001) and more intraoperative transfusions (46 vs. 23%, p=.001) (Table 1).

However, no significant difference was observed for resection of adjacent organs, regardless of the organ (28 vs. 29%, p=.56).

Postoperative outcomes in resected patients (Table 1)

Mortality and morbidity among resected jaundiced patients (n=50)

The postoperative mortality was 16% (n=8). The causes of death were: i/ acute liver failure (n=3) after extended right hepatectomy; ii/ sepsis with multiorgan failure (n=4);

iii/ respiratory distress syndrome (n=1). All 8 jaundiced patients were older than 65 years and 4 underwent major hepatectomy. No risk factor for postoperative mortality was identified in this subgroup of jaundiced patients.

Thirty-one jaundiced patients experienced a complication after surgery. The most frequent complications were biliary leakage (n=12), pulmonary complications (n=11) and sepsis (n=9) and liver failure (n=7). These complications required an invasive

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procedure in 14 patients (reoperation: n=4, radiological drainage: n=8, interventional endoscopy: n=2). The average postoperative hospital stay was 25 days (range: 7-77). On univariate analysis, only preoperative biliary drainage (68 vs. 33%, p=.02) was found to be risk factor for postoperative complications in jaundiced patients. In the subgroup of the 21 patients who underwent extended right hepatectomy, preoperative biliary drainage did not significantly increase morbidity in contrast with the 29 patients with minor hepatectomy (83 vs. 38%, p=.05).

Mortality and morbidity among all resected patients (n=257)

Postoperative mortality and morbidity were 6% (n=16) and 41% (n=105), respectively.

On univariate analysis, risk factors for mortality were jaundice (16 vs. 4%, p=.004), age over 70 years (10 vs. 3%, p=.04) and common bile duct resection (11 vs. 3%, p=.05). Risk factors for morbidity on univariate analysis were jaundice (62 vs. 36%, p=.001), preoperative biliary drainage (68 vs. 39%, p=.002), portal vein embolization (91 vs. 40%, p=.001), major hepatectomy (58 vs. 38%, p=.004), adjacent organ resection (53 vs. 38%, p=.02), portal vein resection (78 vs. 40%, p=.02), common bile duct resection (57 vs. 26%, p=.0001) and intraoperative transfusion (52 vs. 36%, p=.01).

Pathological data -Predictive Criteria of Resectability

Among the 50 resected jaundiced patients, 40 had no proof of cancer prior to hepatectomy. Among the 50 resected jaundiced patients, pathological examination of the specimen was available for only 45 patients. Nine patients had T2 tumors, 19 had T3 tumors and 8 had T4 tumors. For 9 patients, T-stage could not be accurately determined from the pathology report. Thirty-two patients had R0 resection. Among the 41 patients who underwent lymphadenectomy, 19 had lymph node involvement, including involvement of lymph nodes in the hepatoduodenal ligament in all patients and paraaorticlymph node involvement in 2 patients. Seventeen tumors were well differentiated

DISCUSSION

Jaundice is an indicator of advanced disease

Most studies have reported that jaundice is an indicator of advanced disease with a dismal prognosis in GBC. The results of the present study, which is one of the largest studies, confirmed that jaundiced patients had more advanced tumors and poorer 3year survival than non-jaundiced patients (19% and 50%, respectively). The first study focusing on jaundice (3), published by a reference team, reported a 7% resectability rate, a 5% R0 margin rate and poor survival (2-year disease-free survival of 0%, median disease-specific survival of 6 months). These results, emphasizing the fact that resection should not be proposed in patients with GBC associated with jaundice, were largely diffused in the medical community.

Jaundice should not be considered as an absolute contraindication

However, it should be stressed that one of the major criteria (i.e., R0 resection) proposed as a contraindication to resection appears to be over estimated: the 5% R0 resection margin rate was calculated on the whole population of 82 patients and not on the population of resected patients. The real R0 resection rate in the series of Hawkins et al. was actually 67% (4 out of 6 resected patients). Several series also did not report such a poor outcome, with much higher resectability rates ranging from 7 to 53%, and R0 resection margin rates ranging from 15 to 100% (8-12) (Table 3). In the present series, the resectability rate was 45% and the R0 resection rate was 58%. The resectability rate was higher in non-jaundiced patients (64% vs. 45%), but no significant difference of R0 resection rate was observed between jaundiced and non-jaundiced patients (71% vs. 86%). Agarwal et al. did not observe any difference in terms of resectability between resected jaundiced and non-jaundiced patients (27% vs. 36%,

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12 p>.05) [START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF]. The results in terms of resectability can be (artificially) improved by more widespread use of laparoscopic assessment [START_REF] D'angelica | The role of staging laparoscopy in hepatobiliary malignancy: prospective analysis of 401 cases[END_REF][START_REF] Fuks | Role of exploratory laparoscopy in hepato-biliary malignancies[END_REF] especially in jaundiced patients scheduled for surgery due to its accuracy (57%).

Some jaundiced patients appeared to benefit from surgery

Moreover, in the same series [START_REF] Kondo | Factors influencing postoperative hospital mortality and long-term survival after radical resection for stage IV gallbladder carcinoma[END_REF][START_REF] Miyazaki | Radical surgery for advanced gallbladder carcinoma[END_REF][START_REF] Todoroki | Outcomes of aggressive treatment of stage IV gallbladder cancer and predictors of survival[END_REF][START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF][START_REF] Varma | Does the presence of jaundice and/or a lump in a patient with gall bladder cancer mean that the lesion is not resectable?[END_REF], some jaundiced patients appeared to benefit from surgery in terms of survival following resection: with a mean 3-year survival of 20% and some real survivors at 3 and 5 years [START_REF] Kondo | Factors influencing postoperative hospital mortality and long-term survival after radical resection for stage IV gallbladder carcinoma[END_REF][START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF], results never obtained in the subgroup of non-resected jaundiced patients. In the present series, overall survival was better in resected jaundiced patients than in non-resected jaundiced patients (p=.001) and the 3year overall survival rates of 19% was comparable to the overall survival of resected patients with pancreatic adenocarcinoma in whom the principle of curative R0 resection has been established.

Routine sampling of lymph nodes should be performed

The long-term results can also be improved. Firstly, routine sampling of inter-aortocaval lymph nodes was not performed in this study and it is likely that some patients in the subgroup of resected jaundiced patients and poor long-term survival were positive for inter-aortocaval lymph nodes. Inter-aortocaval lymph node sampling must be performed systematically in this setting in order to contraindicate resection. Similarly, in this series, regardless of T-stage, all patients with long-term survival had N0 disease and underwent R0 resection. The results of this study emphasize that hepatic pedicle lymph node sampling may be performed as a routine examination before resection in jaundiced patients with GBC in order to avoid useless surgery in patients with N+ disease (no survivors with N1 disease at 3years). The presence of lymph node involvement has been reported to be a poor prognosis factor by other authors, even in jaundiced patients [START_REF] Hawkins | Jaundice predicts advanced disease and early mortality in patients with gallbladder cancer[END_REF][START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF]. Secondly, only 29% of patients with GBC had adjuvant

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13 therapy in the French nationwide survey of GBC (data not shown) [START_REF] Regimbeau | Chirurgie des cholangiocarcinomes intrahépatiques, hilaires et vésiculaires[END_REF]. A phase III study analysing the effect of adjuvant chemotherapy (GemOx 85) in patients with R0/R1 resection for bile duct cancer is currently underway in France (ACCORD 18/0803 protocol). Inclusion of patients in this study will allow us to address the issue of adjuvant chemotherapy.

Postoperative morbidity and mortality may be decreased by minor resections and careful selection of patients requiring preoperative biliary drainage

However, these encouraging results in terms of survival in resected jaundiced patients were achieved at the price of postoperative mortality and morbidity of 16% and 62%.

The postoperative mortality rate was mainly (50%) due to liver failure and higher among elderly patients after major hepatectomy. In the present series, 46% of patients underwent major hepatectomy. This mortality rate was similar to the mortality observed in other series in which major hepatectomy was performed (3, 8-9, 18) (Table 3). Our surgical practices need to be modified, as it has been reported that the extent of hepatectomy is not related to R0 rate and long-term survival [START_REF] Regimbeau | Chirurgie des cholangiocarcinomes intrahépatiques, hilaires et vésiculaires[END_REF][START_REF] Goetze | Benefits of reoperation of T2 and more advanced incidental gallbladder carcinoma: analysis of the German registry[END_REF]. Secondly, a parenchymal preservation strategy must be investigated in this setting in the light of the results published by Agarwal et al.: in this series of 14 resected jaundiced patients, 13 patients underwent segment IVB-V liver resection with a very low (one patient) mortality, 100% R0 resection rate, and meaningful prolongation of survival [START_REF] Agarwal | Biliary obstruction in gall bladder cancer is not sine qua non of inoperability[END_REF]. A similar strategy of minor resection has been recently published by Chen et al. for hilar cholangiocarcinoma with similar results [START_REF] Chen | Extent of liver resection for hilar cholangiocarcinoma[END_REF]. On univariate analysis, only preoperative biliary drainage (68 vs. 33%, p=.02) was found to be a risk factor for postoperative complications in jaundiced patients. In the subgroup of 21 patients who underwent extended right hepatectomy, preoperative biliary drainage did not significantly increase morbidity in contrast with the 29 patients treated by minor hepatectomy (83 vs. 38%,

Limitations of the study

Certainly, there are limitations to a retrospective analysis conducted on patients treated over a long time interval. Despite the large number of patients included in the study, this was a highly selected cohort, representing only a fraction of the total number of jaundiced patients with GBC diagnosed during the study period. However, by including patients treated at 21 different surgical centers, our results may be less subject to selection bias than previously reported single-institution experiences and may better represent common practice.

Conclusion

The presence of jaundice in patients with GBC does not necessarily indicate inoperability and the decision to contraindicate the only available curative treatment in these patients must be taken very carefully. After laparoscopy and systematic interaortocaval sampling, the population of patients most likely to benefit from surgery must be identified: the subgroup of patients with N0 disease (routine sampling of hepatic pedicle lymph nodes must be evaluated) treated by R0 resection. The results of operative management of jaundiced patients need to be improved in order to decrease the postoperative morbidity and mortality.

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT

  Review Board. Identification of patients was performed by screening the pathology database. The questionnaire was constructed on the basis of the data available in the literature at that time. Investigators were requested to attach an anonymized duplicate of the complete pathology report. All patients who had undergone either curative, palliative or exploratory surgery were further evaluated. Patients were considered to be jaundiced when clinical jaundice was present on initial examination and confirmed by elevated serum bilirubin levels. The diagnosis of GBC was adopted when the pathology report confirmed the presence of adenocarcinoma of biliary origin.

  ). In summary, the morbidity and mortality after resection in jaundiced patients with GBC could possibly be decreased by performing more minor resections and by carefully selecting patients requiring preoperative biliary drainage (especially elderly patients).

Table 1 .

 1 Demographic data of jaundiced (n=110) and non-jaundiced patients (n=319) with gallbladder cancer

	Jaundiced	Non-jaundiced	p-value
	n	n

Table 2 .

 2 Prognostic factors in resected jaundiced patients (n = 50) (univariate analysis) T-stage was not available in the pathology report for 9 patients. Surgical margins were analyzed in all patients regardless of N status.

		n	1-year	3-year	5-year	p-value
			survival	survival	survival
	Gender					.99
	Female	29	49%	11%	11%
	Male	21	48%	36%	36%
	Biliary drainage					.84
	No	22	58%	12%	12%
	Yes	28	41%	18%	18%
	Major hepatectomy					.15
	No	22	60%	25%	25%
	Yes	28	39%	14%	13%
	Main bile duct resection					.76
	No	9	45%	0%	0%
	Yes	41	47%	18%	18%
	Portal vein resection					.48
	No	41	51%	17%	17%
	Yes	9	41%	13%	13%
	T-stage * ♣ ♣ ♣ ♣					.02
	2	9	77%	23%	23%
	3	19	34%	0%	0%
	4	8	0%	0%	0%
	N *					.03
	N0	26	66%	31%	31%
	N1	19	42%	0%	0%
	M					.03
	M0	43	56%	22%	22%
	M1	7	0%	0%	0%
	Surgical margins *					.24
	R0	32	42%	9%	9%
	R1	13	50%	0%	0%
	* Pathological examination was available for only 45 patients. ♣ ♣ ♣ ♣

Table 3 .

 3 Resectability and survival in jaundiced patients in the literature

	Author (inclusion period)	Jaundiced	Resectabilit	R0 resection	Major	Mortality	Lymph node	Survivors at 3
		patients (n)	y	%	resection	%	involvement	years n(%)
			n(%)		%		%
	Hawkins (1995-2002) 3	82	6 (7%)	67*	67	33	-	0(0)
	Agarwal (2001-2003) 11	95	14 (15%)	100	7	7	78	2
	Nishio (1977-2004) 18	96	51 (53%)	100	-	35	-	(41)
	Todoroki (1976-1997) 10	-	61	15	19**	13	-	-
	Kondo (1979-1997) 8	48	-	100	100	27	75	7(22)
	Varma (1996-2003) 12	62	(49%)***	50***	12***	-	-	-
	Present study (1998-2008)	110	50 (45%)	58	46	16	38	4(19)
	* 4 patients had R0 margins among 6 resected patients
	** including non-jaundiced patients with stage IV

*** including patients with abdominal mass

M A N U S C R I P T A C C E P T E D

ACCEPTED MANUSCRIPT 10 and 28 were moderately differentiated. Lymph node involvement was more frequent in jaundiced patients (46 vs. 21%, p=.02). None of the available preoperative criteria was significantly correlated with R0 resection.

Survival data

Survival in jaundiced patients (n=110)

One-, 3-and 5-year overall survival rates for the 110 jaundiced patients were 41%, 15% and 13%, respectively.

Survival in resected jaundiced patients (n=50)

One-, 3-and 5-year survival rates for the 50 resected jaundiced patients were 48%, 19% and 19%, respectively i.e. significantly different from those of non-resected jaundiced patients (31%, 0% and 0%, p=.001). Among the resected jaundiced patients, T-stage, N and M status were found to have a significant impact on survival (Table 2). R0 resection did not increase survival in the overall population of resected patients (Table 2), but R0 increased median survival in the subgroup of N0 patients (20 versus 6 months, p=.01).

All resected patients with T4, N1 or M1 tumors died within the first 3 postoperative years. Eleven resected jaundiced patients were N0R0: 3 patients died postoperatively, 4 survived 12, 15, 20, 22 months, and the remaining 4 patients were real survivors at 5 years. Among these 4 patients, tumor stage was T2 for 2 patients and T3 for the other 2 patients. All of these patients underwent common bile duct resection and 3 underwent in addition resection of duodenum, stomach and portal vein. All these patients had N0 and R0 margins.

Survival in all resected patients with gallbladder cancer (n=257)

Among all resected patients with gallbladder cancer, jaundice was found to have a negative impact on prognosis (Figure 2). Median survival in the presence of jaundice was poorer that of non-jaundiced patients (11 vs. 36

Conflicts of interest:

None of the authors have any financial or personal relationships with other people or organizations that could inappropriately influence (bias) this work.

Responsibility:

This multicenter study is an original work not submitted to any other journal. The corresponding author had full access to all data in the study and has final responsibility for the decision to submit for publication.

Conflicts of interest:

None of the authors have any financial or personal relationships with other people or organizations that could inappropriately influence (bias) this work.