Hervé Chabanne
email: herve.chabanne@morpho.com

Julien Keuffer
email: julien.keuffer@morpho.com

Roch Lescuyer
email: roch.lescuyer@morpho.com

Delegating Biometric Authentication with the Sumcheck Protocol

Keywords: biometrics, verifiable computing, authentication

In this paper, we apply the Sumcheck protocol to verify the Euclidean (resp. Hamming) distance computation in the case of facial (resp. iris) recognition. In particular, we consider a border crossing use case where, thanks to an interactive protocol, we delegate the authentication to the traveller. Verifiable computation aims to give the result of a computation and a proof of its correctness. In our case, the traveller takes over the authentication process and makes a proof that he did it correctly leaving to the authorities to check its validity. We integrate privacy preserving techniques to avoid that an eavesdropper gets information about the biometric data of the traveller during his interactions with the authorities. We provide implementation figures for our proposal showing that it is practical.

Introduction

Motivation

In order to increase the throughput in border crossing, controls operated by officers could be replaced with automated systems. Such systems often use biometrics to authenticate the travellers: a comparison is made between an official document such as a biometric passport and the traveller who needs to prove his identity. However biometric data need to be collected from the traveller to be compared with data stored on the official document and this step of the process can be time consuming. Delegating a part of the process to the traveller can save time but raises a confidence problem: how can the authority be sure that the traveller really ran the computation?

We use verifiable computing as a tool to address this problem. A verifiable computation system allows a verifier to delegate the computation of a function to a prover. Upon completion of the computation, the prover returns the result and a proof of the computation. In our use case, the traveller's smart device has the role of the prover and has thus restricted computational power and storage capacity. We stress that this reverses the classical roles played by the verifier and the prover in most of verifiable computing scenarios, where a weak verifier usually delegates computations to a powerful but untrusted prover. The choice of the underlying verifying system has thus been driven according to this configuration. In particular, the requirements for the prover and the targeted computation led us to choose an interactive proof protocol, namely the sumcheck protocol [START_REF] Lund | Algebraic methods for interactive proof systems[END_REF].

Background on Biometrics

A biometric system is a pattern recognition system, which makes biometric data acquisition from an individual, then extracts a feature set from the acquired data which gives a biometric template. In an authentication scheme,the template is then compared against a referenced template and in an identification scheme it is compared against a database of templates. Due to external conditions such as light, moisture or the sensor used for the capture, two templates computed from the same individual can vary. However, the variation is expected to be small enough to be able to discriminate two templates coming from the same person from two templates coming from different individuals. This is why the comparison of two templates is usually a matching score, reflecting a similarity rate between the two data. A matching threshold has to be defined to discriminate the templates belonging to the same individual or not. Ideally, if the score of two templates is lower than the threshold, they belong to the same individual. However, in biometric systems, two different individuals can have a matching score lower than the threshold, which leads to the definition of the false acceptance rate (FAR) and the false rejection rate (FRR), see [START_REF] Jain | An introduction to biometric recognition[END_REF] for details.

In our scenario, we need an automated face recognition system. Today, many systems performing face recognition use machine learning techniques to transform a face picture into a biometric template. The model called convolution neural network (CNN) [START_REF] Lecun | Gradient-based learning applied to document recognition[END_REF] has shown excellent results [START_REF] Schroff | Facenet: A unified embedding for face recognition and clustering[END_REF][START_REF] Taigman | Deepface: Closing the gap to human-level performance in face verification[END_REF]. CNNs have millions of parameters that are tuned in a learning phase, using a face database for the training. Once the training phase is over, the CNN can embed a picture in a Euclidean space where two vectors representing the same face are closer than two vectors that come from different faces, enabling face recognition.

Background on Verifiable Computation

Although the problem of verifying computations has been theoretically solved with tools from complexity theory and cryptography [START_REF] Arora | Probabilistic checking of proofs: A new characterization of NP[END_REF][START_REF] Micali | Computationally sound proofs[END_REF], new challenges raised by verifiability in the setting of cloud computing recently attracted the interest of researchers. Huge progresses have been made and several research teams succeeded in implementing verifiable computing systems. All these systems start by turning the function to verify into a circuit composed of multiplication and addition gates and then perform verification on the circuit.

A first line of work has built on a refined version of probabilistically checkable proofs (PCP) [START_REF] Ishai | Efficient arguments without short pcps[END_REF] and resulted in a verifiable system called Pepper [START_REF] Setty | Making argument systems for outsourced computation practical (sometimes)[END_REF], which has been refined since [START_REF] Setty | Resolving the conflict between generality and plausibility in verified computation[END_REF][START_REF] Wahby | Efficient RAM and control flow in verifiable outsourced computation[END_REF]. The second line was opened by Gennaro et al. [START_REF] Gennaro | Quadratic span programs and succinct NIZKs without PCPs[END_REF], who achieved a breakthrough by building efficient objects to verify computations called quadratic arithmetic programs (QAPs), resulting in an efficient system called Pinocchio [START_REF] Parno | Pinocchio: Nearly practical verifiable computation[END_REF]. Pinocchio and its refined version [START_REF] Costello | Geppetto: Versatile verifiable computation[END_REF] allow public verifiability: anyone who has access to the public verification key can verify proofs. Moreover, the prover can make his proof zero-knowledge: he supplies a private input to the computation and builds a proof of the correctness of the result without revealing his input to the verifier. Finally, a system called TinyRAM and designed by Ben-Sasson et al. [START_REF] Ben-Sasson | Snarks for C: verifying program executions succinctly and in zero knowledge[END_REF] uses QAPs and has the ability to verify a larger class of computations by modelling programs using RAM. The third line of work relied on the notion of interactive proofs, which was introduced by Goldwasser et al. [START_REF] Goldwasser | The knowledge complexity of interactive proof-systems[END_REF]. In the verifiable computing setting, the verifier checks that the result of the computation is correct during a sequence of interactions with the prover. The more the verifier asks queries, the less the prover has chance to cheat. Goldwasser et al. [START_REF] Goldwasser | Delegating computation: Interactive proofs for muggles[END_REF] introduced an efficient protocol, later optimized and implemented by Cormode et al. [START_REF] Cormode | Practical verified computation with streaming interactive proofs[END_REF]. The last version of this protocol, due to Thaler [START_REF] Thaler | Time-optimal interactive proofs for circuit evaluation[END_REF], is currently one of the fastest scheme for verifiable computing. Furthermore, Thaler proposed an implementation of matrix multiplication and also showed that the the main tool of interactive proofs protocols, namely the sumcheck protocol [START_REF] Lund | Algebraic methods for interactive proof systems[END_REF], can be used to design an efficient protocol for matrix multiplication verification. However all the systems described above are only nearly practical for generic computations. The different systems all have advantages and drawbacks, depending on the type of computations to be verified. One important thing is that all systems building upon PCPs and QAPs need precomputations and amortize their costs by using the verified function several times. The fastest system needs no precomputation and uses the cmt protocol but it cannot handle general computations. Systems based on QAPs and on PCPs have better expressiveness and allow fast verification but the prover's overhead costs compared to native execution of the same computation is consequent. See [START_REF] Walfish | Verifying computations without reexecuting them: from theoretical possibility to near-practicality[END_REF] for comparisons between the different existing systems.

Cormode et al. [START_REF] Cormode | Verifying computations with streaming interactive proofs[END_REF] suggested that the sumcheck protocol could be used to verify an inner product in the setting of data streaming, where the verifier cannot store the inputs and has to update his computations while he is parsing the data. The recent work of [START_REF] Bringer | Some applications of verifiable computation to biometric verification[END_REF] studies the use of verifiable computing for biometric verification in a non-interactive setting i.e. where the prover computes a proof without interacting with the verifier. In contrast, we focus on interactive proofs to design and implement a protocol which aims at verifying several distances used in biometric matchings and adapt the sumcheck protocol [START_REF] Lund | Algebraic methods for interactive proof systems[END_REF].

Use-Case : Fast Border Control

In many places, people living next to another country frequently cross the border with their cars to go to work. We want here to design an automated system to reduce the waiting time, taking profit of the waiting time in the cars queuing line. Our idea is to let the driver perform himself his face verification against his passport photo while crossing the border. Such operations could be performed by a dedicated application installed on his smartphone. At the end, the customs authority will get from this application: a fresh photograph, the official one and a proof that both belong to the same person (Figure 2). A high-level description of our solution (see also Figure 1):

-The traveller (who plays the role of the prover) uses a wireless communication device of the mobile to get the picture stored in his biometric passport. -The picture is turned into a reference template using a CNN.

-The traveller takes a fresh picture of his face and uses the same CNN to create a biometric template. -A biometric matching is performed on the traveller's mobile and interactions between the traveller and the automated border control device lead to a proof that the matching was correctly computed. The interaction begins with the prover sending two templates and the result of the distance computation to the verifier. The proof is stored on the mobile for a later examination.

We emphasize that our contribution is limited to the application of verifiable computation on distance computations involved in biometric matchings. This is only a part of what is needed to address the whole problem. For instance, liveness detection or verifying the CNN output seem necessary but those topics are outside the scope of this paper. Our purpose here is to deal with a realistic use case for a delegation of a verifiable face matching algorithm. Since a CNN embeds a pictures in a Euclidean space, the verifiable biometric matching involves a distance computation which is compared to a threshold. We first show how to verify an inner product and then extend the verification to euclidean distance computing.

The Sumcheck Protocol and Verifiable Distances

In the sumcheck protocol [START_REF] Lund | Algebraic methods for interactive proof systems[END_REF], a prover P wants to convince a verifier V that he knows the value of the expression:

H = x1∈{0,1} x2∈{0,1} . . . xn∈{0,1} g(x 1 , . . . , x n ),
where g is a multivariate polynomial defined over a finite field. If g has n variables, the protocol has n rounds. In each round, the verifier picks a random value Fig. 2. Authentication process between the prover and the verifier from a finite field and challenges the prover to compute a polynomial derived from the initial polynomial to verify. This polynomial is sent by the prover to the verifier and few computations are needed to check that it is linked to the previous one. If the check succeeds, the verifier can accept the new polynomial as a claim for the initial value. At the end, the verifier has to evaluate the original polynomial in a single value to decide if he accepts the initial claim with high probability. This is the only step where the verifier has a computing challenge. . . .

Verifiable inner product

i d ∈{0,1} a(i 1 , . . . , i d ) • b(i 1 , . . . , i d )
To increase the possibility of catching a lie from a cheating prover, the sumcheck protocol uses polynomials defined over a large finite field, which agree with a and b over {0, 1} d and called low-degree extensions and denoted ã and b. The above relation still holds with low-degree extensions of a and b.

Squared Euclidean distance The protocol described in Section 3 can be adapted straightforwardly to verify Euclidean distance. Indeed, given two ncomponents biometric templates a and b, their squared Euclidean distance is:

d E (a, b) = n i=1 (a i -b i ) 2 = n i=1 a 2 i + b 2 i -2a i • b i (1)
Denoting d = log 2 n, we have to verify with the sumcheck protocol the evaluation of the polynomial g over {0, 1} d :

g(x 1 , . . . , x d ) = ã(x 1 , . . . , x d ) 2 + b(x 1 , . . . , x d ) 2 -2ã(x 1 , . . . , x d )• b(x 1 , . . . , x d ) (2)
The same ideas can be adapted to verify the distance involved in iris recognition, which is a weighted Hamming distance [START_REF] Daugman | How iris recognition works[END_REF].

Adding Data Privacy to the Protocol

At the beginning of the protocol described in Section 2, the driver has to send his reference and his fresh templates to the authorities for the verification process. Since biometric template cannot be revoked, we propose to add masking techniques for the templates [START_REF] Atallah | Secure biometric authentication for weak computational devices[END_REF]. In our context, this means that the driver has to pick a random permutation of the template coordinates and a random vector of the same size than the template. More precisely, a template t = (t 1 , . . . , t n ) masked becomes t masked = π(t) + (r 1 , . . . , r n ) where π is a random permutation of the n coordinates and (r 1 , . . . , r n ) is a n components vector of F n p . So if t ref and t are masked with the same permutation and random vector, computing their distance involves computing their difference:

π(t ref ) + (r 1 , . . . , r n ) -(π(t) + (r 1 , . . . , r n )) = π(t ref ) -π(t) = π(t ref -t)
And the scalar product of this difference has the same value than the scalar product computed on the vectors without masks: since π permutes the same coordinates on t and t ref , the difference vector masked is the permutation of the original difference vector and computing the scalar product on this masked vector will give the same result.

The distance computation with masked templates gives information about the distance between the templates and the differences between the coordinates of the templates. But linking these differences coordinates to the unmasked template coordinates is hard because of the number of possible permutations and vectors.

We also stress that the driver has to store the permutation and the random vector. Therefore if the authorities have a doubt about the identity of the driver, the driver has everything on his phone to unmask the templates and compute the distance between them. Similar techniques can be used for iris recognition.

Experimental Results

We implement a verified inner product using the sumcheck protocol, the computations being over the prime finite field F p where p = 2 61 -1. The size of a field element is thus inferior to the machine word size and the probability of being fooled by a dishonest prover is small, see Table 1. Note that optimizations are possible for the verifier but since in our use case the verifier has computational power, we did not implement them.

We run our benchmarks on random vectors of different sizes composed of natural numbers. Dealing with negative numbers or with floating-point rationals is possible with an additional step, e.g. the computations over negative numbers are mapped to computations over a finite field large enough so that the mapping is a one-to-one function [START_REF] Setty | Taking proof-based verified computation a few steps closer to practicality[END_REF]. This step is done before the prove and verify steps. The protocol has therefore to be implemented in a larger field at the cost of a decrease of performances.

Communication costs and security For input vectors of size n, the sumcheck protocol has log 2 n rounds, the verifier sends one field element per round (the random challenge, see Section 3) and the prover three (the three values needed to interpolate round k polynomial). Not taking into account the sending of the input values, we obtain that the total communication during the protocol is 4 log 2 (n) + 1 field elements.

The security of the sumcheck protocol is the probability that a cheating prover builds a proof of a false result that will be accepted by the verifier, this value is given in Table 1 for different input sizes.

Benchmarks We run experiments on a laptop with a 2 GHz Intel Core i5 processor with 8 GB of RAM. The implementation is written in C++. Table 1 gives the average times of 1000 computations for each vector size. We note that this technique does not need the notion of arithmetic circuits. Using the optimized version of the cmt protocol (see Section 1) would lead to a slower protocol with two times more communication costs.

Fig. 1 .

 1 Fig. 1. The biometric matching process

  We now give details on how we adapt the sumcheck protocol to obtain a verifiable inner product and verifiable distance computations. Consider two vectors a, b ∈ Z n . The inner product of a and b is defined by: H = n-1 i=0 a i • b i . Denoting d = log n, the expression giving H can be rewritten, considering a and b as functions defined over {1, . . . , n} such that: a : i → a i and b : i → b i . If the index i is written as a binary vector, i = d k=1 i k 2 k-1 = (i 1 , . . . , i d ) then a and b define multivariate polynomials: a : (i 1 , . . . , i d ) → a i and H = i1∈{0,1}

n

  Inner prod. (ms) Prover time (ms) Verifier time (ms)

					Security Communication
	128	< 10 -4	0.01	0.032	2 -54	232 B
	256	0.0031	0.017	0.053	2 -54	264 B
	512	0.0032	0.042	0.098	2 -53	296 B
	1024	0.0032	0.065	0.25	2 -53	328 B
	4096	0.0077	0.31	1.13	2 -52	392 B
	2 20	3	122	600	2 -51	648 B

Table 1 .

 1 Benchmark of the verified inner product of two n-components vectors

Acknowledgements. This work has been partially funded by the European H2020 TREDISEC (ICT-2014-644412) and the French ANR BIOPRIV (ANR-12-INSE-0013) projects.


Julien Cumin
email: julien1.cumin@orange.com

Grégoire Lefebvre
email: gregoire.lefebvre@orange.com

Fano Ramparany
email: fano.ramparany@orange.com

James L Crowley
email: james.crowley@inria.fr

A Dataset of Routine Daily Activities in an Instrumented Home

Keywords: Dataset, Activities of daily living, Smart home

We present a new dataset, called Orange4Home, of activities of daily living of one inhabitant in a smart home environment. We collected data from 236 heterogeneous sensors in a fully integrated instrumented apartment. Data collection spanned 4 consecutive weeks of working days for a total of around 180 hours of recording. 20 classes of varied activities were labeled in situ. We report the methodology adopted to establish a representative, challenging dataset, as well as present the apartment and sensors used to collect this data.

Introduction

Development, evaluation and comparison of machine learning approaches for activity recognition in smart home environments all require realistic data labeled with ground truth. Acquiring labeled data of activities in a smart home is challenging and costly for a number of reason. For one thing, few instrumented smart homes exist. Furthermore, providing accurate ground truth is costly and tedious. Giving a meaning to data collected by many heterogeneous sensors in an instrumented environment is difficult. For example, finding whether an occupant is currently cooking or not (which might impact the service that the system wants to provide to the occupant), using only low-level sensors such as door openings, luminosity, ambient noise, etc. is challenging. In addition, The range of possible activities is highly variable, and there are no guarantees that activities of an individual in a specific home are representative of the entire population of inhabitants or homes. Thus, establishing a representative dataset of activities in smart homes requires both technical work on instrumenting a home and an important effort to accurately label activities.

In this paper, we present a new labeled dataset, named Orange4Home 3 , of activities of daily living (ADL) of an occupant in an instrumented smart home environment. The Amiqual4Home smart home environment is a fully equipped furnished 87 m 2 apartment, that has been instrumented with 236 data sources, which capture information about use of electrical equipment, water consumption, operation of doors, etc. The facility was constructed to serve as a resource for research in smart home services. We used this facility to acquire data about human daily activities, over a period of 20 working days. Labels for 20 classes of activity were noted in situ by the occupant, representative of the performed activities. This data is designed to be used for supervised offline activity recognition [START_REF] Cumin | Human activity recognition using place-based decision fusion in smart homes[END_REF], supervised online activity recognition [START_REF] Ordóñez | Deep convolutional and lstm recurrent neural networks for multimodal wearable activity recognition[END_REF], unsupervised activity discovery [START_REF] Cook | Activity discovery and activity recognition: A new partnership[END_REF], activity prediction [START_REF] Li | Prediction of human activity by discovering temporal sequence patterns[END_REF], as well as other applications.

We report in Sect. 2 related datasets of activities in the home. We present in Sect 3 the methodology adopted to establish a realistic dataset of labeled activities, and in Sect. 4 the technical aspects of the experiment. We conclude in Sect. 5 on future uses of this dataset.

Related Work

The dataset presented in this work complements the already significant number of existing datasets of ADL, such as the Opportunity dataset, the Transfer Learning dataset, and other datasets of ADL.

Opportunity [START_REF] Roggen | Collecting complex activity datasets in highly rich networked sensor environments[END_REF] is a dataset where activities of 4 different occupants are recorded using a high number of both environmental (i.e. fixed in the home) sensors and body-worn (i.e. placed on the occupant) sensors. This dataset provides 3 levels of labeling of activities, from atomic arm gestures to high level activities such as eating a sandwich. However, the Opportunity dataset was recorded in a single experimental environment of only 1 room, which lessens its representativeness of real, inhabited homes. Moreover, nearly half of the sensors used are body-worn sensors, which is not realistic for smart home systems aimed at the general population, which is what we are interested in in this work. Finally, the sequence of activities captured in this dataset are very limited in time (about half an hour).

The Transfer Learning dataset [START_REF] Van Kasteren | Transferring knowledge of activity recognition across sensor networks[END_REF] is another dataset of activities of daily living, recorded in 3 different real homes inhabited by 3 different persons. Labeling was done in situ by the occupant for a period of 13/18/25 days respectively, depending on the home. This dataset unfortunately contains the labeling of only 8 classes of activities (not including an "Other " activity), which may be too limited to be representative of all significant activities of a home. Moreover, only 23/21/14 sensors respectively were present in each home, which is possibly too little to realistically represent the complexity of future smart home systems.

ARAS [START_REF] Alemdar | Aras human activity datasets in multiple homes with multiple residents[END_REF] is a dataset of activities of daily living recorded in two real houses for a full month. This dataset contains the labels of 27 different activity classes labeled in situ by the inhabitant to a good degree of accuracy. Each house was equiped with 20 binary sensors, which is unfortunately restrictive in terms of algorithmic evaluation: it is not possible to use this dataset to experiment on algorithms that deal with heterogeneous data, nor is it possible to study sensors redundancy due to the small number of sensors.

A dataset by Tapia et al. presented in [8] provides the recordings of 77/84 sensors respectively in 2 real homes, inhabited by 2 different persons, for a period of 14 consecutive days. 33 different activities are labeled, each being part of categories of activities. This dataset was recorded with the intent of evaluating recognition of activities useful to healthcare applications, such as care to elderly people, which makes its representativeness of systems aimed at the general population debatable. Moreover, the authors of this work report significant difficulties in in situ labeling of activities, which was too coercive for both occupants, leading to imprecise or missing labels which had to be fixed by hand after the experiments.

The MavPad 2005 dataset [START_REF] Youngblood | Data mining for hierarchical model creation[END_REF] is a dataset recorded in a student apartment instrumented with 76 sensors of various kinds (light, temperature, humidity, motion, doors, water leak, smoke and CO 2 ), for a duration of 7 weeks during which one occupant was present in the home. This dataset is unfortunately not labeled with activities, which limits its usefulness to applications such as sensor events prediction, while not being usable for activity-related problems.

In this work, we aim at recording a dataset of activities which combines the positive points of these state-of-the-art datasets into one: our dataset provides the recordings of a high number of heterogeneous sensors scattered seamlessly in a real home, labeled in situ with a significant number of representative classes of activities performed by one occupant for a duration of 20 days.

Methodology

Goals of the Experiment

Based on the positive and negative points of state-of-the-art datasets of activities in the home, presented in Sect. 2, we based our methodology for recording the Orange4Home dataset on the following goals that we intend to reach:

1. label accurately all 4 main context information of the home for the entirety of the experiment; 2. record realistic routines of daily living of the general public (i.e. not of a specific population such as elderly people); 3. record data in a realistic environment, which is as close to a real home as possible; 4. record data in a pervasively instrumented environment, where as many objects as possible are instrumented, with as many different types of sensors as possible; 5. record data on a sufficiently long time scale such that the dataset is usable to test activity prediction approaches.

To fulfill goal 1, we need to provide information of identity, time-of-day, place and activity [START_REF] Cumin | Human activity recognition using place-based decision fusion in smart homes[END_REF]. The Orange4Home dataset contains all 4 information, as there is only one occupant (identity is thus unique), all events are timestamped, and both place and activity are labeled in situ by the occupant (see Sect. 4.3).

The experiment spanned 4 consecutive weeks of working days, in order to fulfill goal 5.

We present in Sect. 4.1 the instrumented apartment used as the recording environment to fulfill goal 3, and in Sect. 4.2 the sensors and data types recorded during the experiment to fulfill goal 4.

To fulfill goal 2, we need to establish a home occupancy scenario, which will guide the choices of routines the occupants need to perform. We present this scenario in Sect. 3.2.

Home Occupancy Scenario

In this experiment, we imagine that the home is a coworking apartment in which the subject of the experiment, Bob, comes to work alone every working day, from around 08:00 to 17:00. This apartment is a pervasive environment filled with sensors of various kinds, which transmit their data to a centralized system in charge of the home.

Bob is interested in having personalized services in this coworking environment, based on his activities. As such, he will label his routines for a duration of 20 days (i.e. 4 weeks of working days). Since this is Bob's coworking apartment, his activities will not only be work-related, but also lunch and leisure related.

Bob does not live in the home outside of working hours, since this is a coworking environment. Therefore, data outside these hours is not provided.

Activities in Orange4Home

As mentionned in Sect 3.1, identity, time-of-day, places and activities are key information of context. Identity is both the identity in the literal sense of an occupant, but also their social role in the home. Time-of-day can be any semantic temporal information such as a part of the year, whether it's a week day or not, etc. Places is a geographical location in the home which holds a specific function for the occupant, such as the bathroom or the kitchen. An activity is a set of tasks (or operations), a task being a set of actions [START_REF] Crowley | Perceptual components for context aware computing[END_REF].

Selecting the actual sets of labels used in the dataset for identity, time-ofday and place values is rather direct: names, timestamps and rooms of the home, respectively, are sufficient, since we can extract semantic labels from those values (e.g. all semantic labels for time-of-day can be obtained from a timestamp). It is less clear what set of labels should be used for activities. For example, in the Opportunity dataset [START_REF] Roggen | Collecting complex activity datasets in highly rich networked sensor environments[END_REF], there are 3 levels of activity labeling, from complex activities like "Sandwich time" to atomic gestures like "Interact with the bottle with the left arm" (which match the activities, tasks and actions hierarchy).

In this dataset, we only label activities. Actions do not carry any functional meaning and are therefore not useful labels to characterize context in the home. Tasks, like activities, do carry functional meaning, but we believe that contextual information provided by tasks is too limited for general-purpose context-aware services (but could be useful for specific applications). Furthermore, tasks and actions are too numerous and possibly too short-lived to be effectively and accurately labeled, be it from an occupant in a real-world setting, but also in an experimental setting of data collection.

The activities we aim to record are those that are quite frequent, and fairly recurrent in time. They must also fit the scenario established in Sect. 3.2. We present below the list of activities, grouped by places (see Fig. 3 and Fig. 4) in which they can occur:

-Entrance Entering, Leaving; -Kitchen Preparing, Cooking, Washing the dishes; -Living Room Eating, Watching TV, Computing; -Toilet Using the toilet; -Staircase Going up, Going down; -Walkway (no activity specific to this place); -Bathroom Using the sink, Using the toilet, Showering; -Office Computing, Watching TV ; -Bedroom Dressing, Reading, Napping; -Common to all places Cleaning.

We have established this list of activities based on the existing places and appliances available in the apartment, such that all realistic and common classes of activities that are usually performed in a coworking home are represented in the dataset. We have also tried to balance classes such that no place contains the majority of classes.

As we can see, some activities can occur in multiple different places (e.g. Watching TV in both the Living Room and the Office, Using the toilet in both the Toilet and the Bathroom, etc.). It is very common for occupants to be able to perform certain activities in multiple different places, which is not a possibility often captured in state-of-the-art datasets of ADL. Our experiment is set in a real home, in which forbidding those situations would not be realistic; allowing that some activity classes can happen in different places also adds complexity to the dataset, making it more challenging as a benchmark for ADL-related algorithmic problems.

There is no trivial link between activity and sensor data in the general case. Activities can vary in duration and in the way they are performed by the occupant. For example, the activity Preparing will be heavily dependent on what the occupant is intending to cook: differences in which cupboards are opened and in what order can for example appear. The occupant can also do mistakes or change their mind on what they want to do in this activity, adding more sensor events.

occupant's Routine in Orange4Home

The experiment ran from January 30 th 2017 to February 24 th 2017, during working days: 08:00 to 17:00 on average, from Monday to Friday. Since the occupant is not normally working in this apartment, imposing a specific routine to the occupant is a necessity. Indeed, with very limited familiarity with the home, and with only 20 working days of experiment, an occupant might have the tendency to limit their activities to those they do in their own home and workplace, or with appliances that they are familiar with (although a mock experiment for a single day was performed prior to the real experiment so that the occupant gained more familiarity with the home). Moreover, imposing a routine on the user allows us to make sure that all activities are sufficiently represented in the dataset (so that it is for example usable with supervised machine learning techniques) and that sequences of activities are sufficiently frequent so that the dataset can be used to experiment activity prediction approaches.

The planning has been established around a standard day routine, presented on Fig. 1. This standard day routine has been carefully established with the following goals in mind:

this routine must contain all activity classes (except for Using the toilet which is unpredictable); this routine must span an entire working day; this routine must fit our coworking scenario presented in Sect. 3.2. The standard day routine chosen therefore includes the occupant showering, using the sink and watching TV news in the morning, cooking and eating their food in the apartment, spending leisure time after lunch on their computer, reading and napping, and spending the rest of their time during the morning and the afternoon working on their computer in the Office. This routine is strictly followed during the first two weeks (with leniency on the times at which activities start and end, and with slight differences on Fridays), and minor to major changes (such as interversion, omission, shortening, etc. of activities) to this daily routine are applied to establish the planning for the last two weeks. For example, we present on Fig. 2 the daily routine followed on Tuesday of the fourth week (February 21 st , 2017). We can see fairly significant deviations from the standard daily routine this day: the occupant leaves the home at lunch time, the occupant does not perform any of the leisure activities during the lunch break, but instead goes back to work upon reentering the home (after the activity Using the sink ).

This way, the dataset contains a routine of sufficiently recurring activities in the first 2 weeks, while also containing minor to major variations on that routine in the 2 last weeks; this allows the dataset to be used as a challenging benchmark, not only for activity recognition problems but also for problems of activity prediction in time (over minutes, hours, days or even weeks time scales), with any type of algorithmic approach including supervised models. The variations in the last two weeks prevents activity prediction from being a trivial task with this dataset, while maintaining realism and coherency in the way routines evolve from one week to another.

4 Data Collection

Overview of the Apartment

The Amiqual4Home project4 is an experimental platform which comprises prototyping workshops, living labs and various mobile tools to be used in ambient intelligence research projects. Among those living labs, there is an instrumented apartment5 : an 87 m 2 two-story home fully instrumented with sensors and actuators of various kinds throughout its rooms. The purpose of this apartment is to provide an environement in which to experiment on smart home systems in a real setting of an instrumented home. In particular, it can be used to record sensors' data during long periods of inhabited times, as was done in this work. Figure 3 and Fig. 4 presents the layout of the apartment, annotated with the names of places of the apartment.

Sensors and Data Collection

The apartment has been furnished with the explicit goal of being an experimental apartment; as such, it is instrumented with many fully integrated sensors that are either not visible or not a hindrance to the occupant, as opposed to sensors installed in a standard apartment. The extensive list of sensors provides many different kinds of data, such as doors or cupboards opening, ambient noise, temperature, CO 2 levels, presence, switches being pressed, electrical information about appliances, hot and cold water consumption, luminosity, heaters information, weather information, etc. Moreover, all sensors are associated to the room they are installed in (or to the entire apartment, if it is a global information about the home). A total of 236 different data sources are present in the dataset. OpenHAB6 is used to collect data from all those sensors during the experiment. A MySQL7 database is used to persist the data collected by openHAB. Videos from cameras placed on the ceiling of most rooms were also recorded to serve as ground truth; they were used to correct the few labeling mistakes made during the experiment, but are not provided in this dataset.

We present in Table 1 the number of sensors in each of Orange4Home and for each of the 4 main types of data produced by sensors: binary (door opening, presence, switches, etc.), integers (total cold water consumption, appliance power, humidity, etc.), real numbers (luminosity, voltage, CO 2 levels, noise levels, etc.) and categorical data (weather, heater modes, AC modes, wind direction, etc.). We can see that there are large variations in the number of sensors per place, and on the types of sensors per place, which is expected because each place has a different use and thus different objects that need to be instrumented. We can also observe that all 4 types of data are well-represented, making Orange4Home a dataset of truly heterogeneous sensors.

We present on Fig. 5 and Fig. 6 the number of presence detections and the power consumption of the computer in the Office during the first 5 days of experiment. We can observe that both sensors provide valuable information for activity recognition: both sensors capture correctly that something is happening in the Office on mornings and afternoons, while nothing happens during the lunch break (there are data during the lunch break on Friday because the lunch break on Friday is shorter, and thus does not cover an entire hour interval). We expect that data from all sensors is sufficiently rich to capture all activity classes performed during this experiment. There are no body-worn sensors in this dataset. We indeed believe that bodyworn sensors are not a realistic data source to use in a smart home system intended for the general public, where data collection should be as seamless as possible (as opposed, for example, to healthcare or wellness systems, where trading seamlessness for more health-related data sources is desirable). Smartphones could be an example of realistic body-worn data sources; however they are not necessarily always carried or even owned by an occupant, and are thus not included in this dataset.

In Situ Labeling

Labeling of activities was performed in real time by the occupant, using an Android application on a smartphone that the occupant carried throughout the home. This application sent events of virtual sensors (one for labels and one for comments) to OpenHAB's APIs through WiFi.

This application allows the occupant to select the room they are in, and then selected the activity they will perform (the set of activities being restricted to those that can happen in the selected place). The occupant can then press the "START " button before beginning their activity, and the "STOP " button (which appears in a modal window) once the activity ended. The application also allows the occupant to send comments through the "ERROR" button. This was used to comment any unexpected event (such as the occupant pressing "STOP " later than the actual end of the activity), in order to greatly simplify the task of fixing labeling issues (which there were very few of) after the experiment.

We present in Table 2 the number of instances of each class of activity that was labeled during the 20 working days of data collection. We can observe that some activity classes are way more numerous than others (e.g. Computing in Office compared to Cleaning in Bathroom), which is also a reality in a real home setting. No activities other than those presented in Table 2 this was never needed). 493 instances of activities were performed in total during roughly 180 hours of experiment, for a total of 21 MB of data (in a MySQL database dump format).

Postprocesses

Electrical consumption data for the connected plugs of the computer and the TV, in both the living room and the office (5 plugs in total), have been simulated for the first day (30 th of January) of the experiment, using averaged data from other days of the experiment. Those plugs were indeed non-functional this day. Data from those plugs were also filtered to remove sporadic outliers most likely induced by intrinsic problems with the plugs.

Events are persisted at most every second for a sensor; therefore, if two events happened during the same second (such as pressing and releasing a switch), the first one was persisted one second earlier than the second event.

Apart from the previous two points, no other postprocesses were applied to the data. In particular, we report no missing sensor values for the entirety of the experiment, thanks to the constant and extensive work done in maintaining the experimental apartment for the sake of the Amiqual4Home project.

We presented in this paper a dataset of labeled activities of daily-living of an occupant in a fully-integrated, instrumented smart home. This dataset spans 20 working days of realistic routines and contains 236 heterogeneous data sources capturing an extensive amount of events happening in the home. Experimenting in a home that the occupant is not used to forced us to carefully craft routines of activities (the process of which we have reported here) such that the occupant feels comfortable and confident enough to act as if they were in their own home.

We believe this dataset can be used as a realistic benchmark for various different kinds of algorithmic problems we are facing in smart homes: activity recognition, activity segmentation, etc. In particular, the length of the experiment as well as the established routine and its variability makes this dataset a good benchmark for activity prediction in smart homes for different time scales.

Fig. 1 .

 1 Fig. 1. Standard day routine. Activity is indicated on the left side, and the place in which they are performed on the right side.

Fig. 2 .

 2 Fig. 2. Routine for February 21 st , 2017. Activity is indicated on the left side, and the place in which they are performed on the right side.

Fig. 3 .Fig. 4 .

 34 Fig. 3. Ground floor of the apartment

Fig. 5 .

 5 Fig. 5. Presence in the Office during the first week (each box is a 1 hour interval).

Fig. 6 .

 6 Fig. 6. Power consumption of the computer in the Office during the first week (each box is a 1 hour interval).

Table 1 .

 1 Number of sensors per place and per type of data in Orange4Home.

				Data type
	Place	Binary Integer Real number Categorical Total
	Entrance	3	1	2	3	9
	Kitchen	13	21	18	0	52
	Living room	16	6	8	7	37
	Toilet	3	1	1	0	5
	Staircase	3	0	0	0	3
	Walkway	9	0	1	0	10
	Bathroom	9	6	8	3	26
	Office	9	3	3	5	20
	Bedroom	17	4	6	7	34
	Global	1	13	20	6	40
	Total	83	55	67	31	236

Table 2 .

 2 were performed (the occupant could select an activity named Other in the labeling application, but Number of instances of each class of activity.

	Place	Activity	Number of instances	Total
	Entrance	Entering	21	42
		Leaving	21
	Kitchen	Preparing	19
		Cooking	19	61
		Washing the dishes	19
		Cleaning	4
	Living room	Eating	19
		Watching TV	18	71
		Computing	15
		Cleaning	19
	Toilet	Using the toilet	8	8
	Staircase	Going up	57	114
		Going down	57
	Bathroom	Using the sink	38
		Using the toilet	9	70
		Showering	19
		Cleaning	4
	Office	Computing	46
		Watching TV	14	64
		Cleaning	4
	Bedroom	Dressing	30
		Reading	15	63
		Napping	15
		Cleaning	3
		Total		493

http://amiqual4home.inria.fr/orange4home

https://amiqual4home.inria.fr/

http://amiqual4home.inria.fr/tools/smart-home

https://www.openhab.org

https://www.mysql.com

Acknowledgments. We thank Nicolas Bonnefond and Stan Borkowski for their technical and organizational help. This work benefited from the support of the French State through the Agence Nationale de la Recherche under the Future Investments program referenced ANR-11-EQPX-0002.


Ancient medicine, humanistic medicine: the Renaissance commentaries of Galen, transmission and transformation of knowledge

The sixteenth century was a period of "rediscovery" of the Greek language, philosophy, literature, science and medicine in Western Europe. Learning Greek was first of all intended for shifting the focus of religious conceptions through a personal approach to the original text of the Bible in accordance with the principles of the Reformation, but all Greek texts, first of all the scientific and medical ones, took advantage of this new situation. Galen's treatises, regarded as a fundamental part of medical education, had already been translated into Latin, commented and included in the university curricula of the Middle Ages. Yet there were new translations and commentaries by Renaissance humanists, who knew Greek and were able to read Galen "in the original", and who regarded themselves as heirs of the ancient Greek medicine: transmission through translation and commentary became a part of a "continuum". The purpose was to facilitate the study of these treatises by students whose knowledge of Greek remained inadequate.

Our study will focus on two commented editions of Galen's De morborum differentiis/causis, De symptomatum differentiis/causis. The first one (Lyon, 1540) contains the Latin translation by Guillaume Cop and the commentary by François Valleriole, a French physician of Arles. The second one (Paris, 1550) contains the Latin translation and commentary by the German humanist Leonhart Fuchs. Our first purpose is to compare the two translations, the one of Cop and the one of Fuchs, in order to study the relationship of each translator with the Greek language. The second purpose is to compare the two editorial projects, including the attitude of Valleriole and Fuchs toward Medieval, mostly Arabic, tradition. The third purpose is, by using passages about for example birth and young children, the role of women, or the excretion process (evacuation of "superfluous" substances), as well as passages relating the personal experience (practice of medicine), to point out how those humanists, who were medical teachers, physicians and learned men as well, (re)shaped and adapted ancient medical knowledge, continuing and renewing the doctrine of Galen. Also to point out how they switched code from medical to social or moral concerns.

Let me introduce the three characters of my story, in chronological order

The first one, Guillaume Cop (or Copus), 1450-1532, was born in Basel, but he spent almost all his life in France and took an active part in the French humanistic movement: as a teacher, teaching medicine in French in Paris, to "barbers-surgeons" included, and thus being in rivalry with the Sorbonne authorities who forced him to cease this activity; as a court physician; as a friend of leading figures of the French humanism, such as Guillaume Budé or Lefèvre d'Étaples; as an active contributor to the foundation of the Collège Royal (nowadays Collège de France; e.g. when he tried to convince Erasmus to come to Paris and join the team), founded in 1530 by François 1er, in order to minimize the influence of the conservative Sorbonne and promote new languages such as Greek and Hebrew. Copus' translation of Galen and of other medical treatises (Hippocrates, Paulus of Aegina) is a faithful one, but also a Latin text emancipated from its Greek original, a regenerated language.

The second one, François Valleriole (1504-1580) is a commentator using the translation of Cop. He was born in Montpellier, where he studied medicine, and he spent almost all his life in Arles, a city in the south of France, as a practicing physician. At the age of 70, he became a professor of medicine in Torino. Studying medicine in Montpellier undoubtedly played an important role concerning his interest in Galen, as well as in Arabic treatises which he seems to know fairly well: Galenism has been developed since the Middle Ages, thanks to Arnaldus de Villanova1 (1240-1311) who, as a university rector, introduced the concept of "the new Galen", a rationalistic and scientific approach to medicine through the study of some 35 works either written by Galen or attributed to him, and an Arabic medical corpus (Avicenna, Rhazi, Al-Kindi, Averroes). Valleriole is a man deeply rooted in his region, without being a "regionalist". It is one of the characteristics he shares with Leonhart Fuchs.

The German Leonhart Fuchs (1501-1566), born in Tübingen where he spent almost all his life teaching medicine in the university, is a Hellenist and a Hebraist, taking an active part in the Lutheran Reformation where ancient languages had to be a part of the theological education, of the new religious ideas. He is well known as a botanist, being regarded as the father of the modern botany, as an anatomist, introducing the anatomy of Vesalius in Germany (1551 Epitome de Humani corporis fabrica ex Galeni et Andreae Vesalii libris), and as a polemist, like Galen: vehement against his fellow humanists (e.g. Cornarius furens 1538), but above all against Arabs.

Comparison of the two translations, Cop and Fuchs

Despite the fact that the image of a "universal" European culture, across the borders of countries, sounds like a fairly idealistic concept, it cannot be denied that the Renaissance humanists in France, Germany or Italy shared similar cultural and scientific concerns, traveled all over the continent in order to communicate with other scholars or teach in the universities, and thus developed a more "open" concept of science and culture. They shared two languages as well: Greek, which they wanted to "bring back to life", and Latin as a lingua franca in order to facilitate exchanges. What is interesting to examine here is the evolution of the relationship between those two languages in the course of time: in the beginning and until the middle of the 16 th cent., there was hope of a potential generalization of Greek, which was supposed to become a common scholar language; Latin was regarded as "inevitable", because the majority of students (and even scholars)

did not yet know Greek, and therefore translations from Greek to Latin were necessary; as the time went by, things changed partly because the influence of vernacular languages increased, and partly because there was no generalization of the influence of Greek. All students were not able to study Greek texts "in the original". Greek remained a "learned" language, and Latin did not disappear.

Both translations are faithful to the Galenic Greek text, but each translator has his own way to transmit text and therefore ideas.

Cop is producing a really new text, which does not remind us of the Greek original, which is the case with Fuchs' translation. This can be noticed firstly by examining syntax: Cop makes frequent use of subordinate clauses, of what is called, according to the Aristotelian rhetoric term, a "periodic" style, κατεστραμμένη λέξις, while Fuchs remains close to the Greek parataxis, εἰρομένη λέξις. Secondly, their stylistic particularities shed light on their different approach (or appropriation) of the Greek text: stylistic devices such as litotes or periphrasis make the text of Cop more "literary" and less austere, more pleasant for the reader, even if the result is somewhat far from the original Galenic text. Fuchs' style is extremely simple, unadorned, perhaps because he is more interested in correcting the Greek text of the Aldine edition, or because his milieu is less concerned about reflections on language.

On the one hand the result concerning Cop is an autonomous Latin text, which adapts Galen without betraying him, and which, according to my experience as a translator, would be more helpful if we want to translate Galen into French. The translation of Cop can also be regarded as a part of a broader humanistic concern about the transition from Greek to Latin and from Latin to vernacular languages, a reflection prompted mostly by the French poets of the Pléiade. On the other hand, Fuchs' translation, even if his Latin can be read independently without being a "carbon copy" of the Greek text, shows less linguistic and more textual concern, and tends to stress medical education: translation as a tool for doctrine and practice, Galen as the authority medical students must lean on. Some examples:

(tables 1 and 2)

Two editorial projects

The examination of Valleriole's and Fuchs' dedicatory epistles and prologues, as well as some of their intertextual references in the commentary, sheds light on their aims as translators and commentators, as humanists and learned men, in the framework of the Western Renaissance.

A more or less exhaustive survey of their statements produces first of all the traditional humanistic topics as common ground between the two editorial projects.

Both humanists are looking for "truth", veritas, and want to stimulate all the veri studiosi in this search. "Truth" stems from ancient texts, literature, philosophy, medicine, that is why the continuity of learning is so important, and the role of Galen instrumental.

Translating and commenting has also a pedagogical goal: Galen must be within reach of anyone who wants to study medicine; students ought to regard his treatises as a major part of their education. It is important to make the right choice: the one of study instead of social whirl, power and glory.

Their principal differences:

According to Valleriole, new, improved commented editions of Galen are needed, the existing ones being insufficient in quantity and quality. Fuchs insists on the Greek sources: he encourages his reader to collate Greek manuscripts and editions. Valleriole wants to turn his own spare time to advantage for the community: as the past winter was fairly clement, he spent less time healing patients than studying ancient medicine. It is time to share his learning with his readers. Fuchs warns scholars and students against the "noxious" influence of Arabic medicine, and the errors of Arabic translations and commentaries. "Arabic" means "Latin" translations, made "in the past" by scholars who did not know Greek. "At the present time", according to Fuchs, "Arabic" texts must be rejected, as Greek ones are available. Fuchs thus prepares his reader for a personal approach to the Galenic text: the translator is a mere "mediator" or "facilitator".

Valleriole puts forward his pleasure as a commentator and a scholar. Sharing pleasure is as important for him as sharing learning.

1. How does the editorial project work in the field of words?

Both commentators provide a lot of terminological explanations, which is fairly common for any commentary. As they address readers who were supposed to be less familiar with Greek than with Latin medical terminology, they both explain Greek terms, frequently printed in Greek in the commentary, by giving the Latin equivalent (word or periphrastic explanation). Valleriole systematically appeals to Arabic terminology (Latin Arabic), in some cases Averroes, but mostly Avicenna whom he seems to know very well: he makes precise and sometimes detailed references to his treatises. Valleriole had studied in Montpellier, where those treatises were a part of the medical curriculum and continued to be studied for a long time after their introduction by Arnaldus of Villanova in the 13 th cent.

(table 3)

Instead of trilingual terminology, Fuchs leans on lexicographical or encyclopedic authorities in order to give useful details about words: he frequently refers to the Souda or to what he calls "Phavorinus", the Greek lexicon ( 1523) by the Italian Hellenist Favorino Varino (or Guarinus Camers, 1450-1537). But the most important point for him is the emendation of the Greek text. He corrects some errors discovered in the Basileensis, the Aldine edition of 1538 in which he took part. A parallel can be drawn between Fuchs and Niccolò Leoniceno, the first Latin translator of those four Galenic treatises: they are both interested in philological issues.

The peculiarity of Valleriole in discussing Greek and Latin is that he regards as "ridiculous" a preference for the Latin term, when the Greek one is available even in Latin: he gives advice to the reader/student/scholar in order to make the accurate choice, e.g. in the case of "trembling" (rigor, not horror), "mania" (mania, not furor), "symptom" (symptoma, not accidens).

2. How does the editorial project work in the field of ideas?

Attitude towards tradition

Valleriole refers frequently to the Arabic tradition, not only through terminology, but also in order to comment on doctrinal points. He does not reject this medical or philosophical tradition; he sometimes considers it to be instrumental in comprehension.

After a survey of those references, too many to be cited here, we notice that the Arabs are complimented when they agree with Galen: they share the same logical method, the same doctrine about the mix of the four elements, they condemn drunkenness etc. In case of disagreement, the Arabs are criticized more or less severely; the advantage goes to Galen: Avicenna makes an error concerning the attraction of the healthy part of the body by the weak one (the right Galenic statement is the opposite one); Averroes misjudges Galen, pretending that he does not refer to cases of dangerous menstrual flow; Rhazi "is not ashamed" to claim that Galen's doctrine about the decrease of the pupil (provoked by both dryness and moistness) is false.

Fuchs' anti-Arabic statements are fairly well known. Yet he scarcely refers to Arabic terminology or doctrine in his commentary, criticizing it, but with less vehemence than in his epistle and prologue. Arabs are "noxious" not only because of their bad translations and erroneous doctrine, but also because they represent the Medieval "past" and the "Oriental" threat. The continuum from Greece to Renaissance excludes Arabs, as if their translation movement never existed, as if they were completely ignorant of Greek manuscripts and texts. The linguistic and doctrinal errors of the Arabs are detailed in his Paradoxa medicinae (ed. 1535 and 1555).

Medicine and society, medicine and morality

Valleriole has been an active physician all his life. Therefore, it is rather frustrating to have so scarce references in his book concerning medical practice. Perhaps he does not want to "glorify" himself: glory, medical skill, achievements belong to Galen. Perhaps this scarcity matches with the nature of the treatises he is commenting on: the principal theme is nosology, not method of healing. There are, however, at least three relations of personal experience worth noticing: Galen thinks that there are some very rare occasions of healing fatal wounds of the head, and Valleriole refers to an old woman of Avignon healed by him; Galen explains "hot" diseases such as sunstroke or fever, and Valleriole refers to the Tullensis episcopus he healed; the relation about diseases of the "authoritative functions" (τῶν ἡγεμονικῶν) gives Valleriole the opportunity to remind us the "handsome and kind young girl of good morals" he healed.

What is not personal medical experience but personal interpretation of the Galenic text and code switching from medical to moral pertains first of all to women, who are "naturally" to be kept under surveillance. We notice that Valleriole, but also Fuchs, switch the tone of the commentary according to what is at stake. Children, women and maternity are serious concerns that need attention.

Galen (7, 27-29) warns against malformations of infants and young children, and gives advice on how to avoid them. He points out the responsibility of midwives and wet nurses whose duty is to take care of those "fragile" and "moist" little human beings. As medical (or paramedical) professionals, midwives must acquire skill in order to correctly receive the newborn child at the very moment of birth. Nurses and wet nurses must learn how to swaddle carefully, especially girls. Valleriole's recommendations are not about professional skill: he addresses parents and gives them a list of criteria for the "good wet nurse" (a healthy and a virtuous one), but he contradicts himself, because he first of all recommends maternal breast feeding, considered to be a moral obligation for all women of good physical condition. A "bad" wet nurse (morally reprehensible) transmits "bad" morals by means of her milk. Concerning swaddling, Valleriole gives no advice, but makes some references to Christian authors (Prudentius, Jerome, Augustine) who criticize women's appearance, artificial beauty: it is a plea in favor of female simplicity. Fuchs also criticizes ridiculous feminine appearance due to bad swaddling by wet nurses: he refers to Roman comedy (Terence), in order to mock women's lack of femininity (a young girl who is like a pugilist).

Galen's issue is about how to avoid women's "bad humors", especially in the period of pregnancy when they suffer from deprived appetite (the disease called pica, κίττα/κίσσα, 7, 133), his advice to be careful about what to eat, and his explanation about how to prevent the embryo's dyscrasia resulting from the deposit of "superfluities" (περιττώματα) in two membranes and from "abnormal" maternal food drawn into its veins. Valleriole's issue is a caveat (cum Galeno duce cavendum): according to him, pica is an exclusively feminine disease; women affected are compared to chattering birds "pica, garulissima aves" or to the parasite plant called κισσός (ivy). Women do not seem to be aware that their bad nutritional habits (when they chose food according to their pleasure) compromise the health of the embryo, "an innocent creature which cannot implore help". Women are suspected of yielding to their own desire and pleasure, and not accomplishing their maternal duty.

Galen's issue about "nature" and "causes of symptoms that are contrary to nature" (7, 148) is a typical medical one. Later on (7,(208)(209) he examines troubles of digestion due to "excessive amount of food and drink, or abnormal quality, or inappropriate time or improper order", and explains the term "improper order" by giving some examples of food taken "in disorder", and "inappropriate time": "apples and pomegranates first, and vegetables with olive and fish oil last", breakfast taken in the early morning "before the previous food had been properly passed on". Valleriole insists on damage caused by an excessive way of life. He comments on the Greek aphorisms "know thyself" (γνῶθι σεαυτόν) and "nothing in excess" (μηδὲν ἄγαν), and addresses directly the reader, tu, who must be conscious of the "fragility" of the human body, whose health can only be preserved by means of a healthy life. He switches again to moralizing remarks against laziness, greed, and vice that provoke diseases. His vehement criticism of gluttony and intemperance targets all those people who spend their time in ientaculis, compotationibus, prandiis, merendis, coenis, antecoeniis, et comissationibus. Such behavior not only causes diseases, but also divine hatred, regarded as a transgression of (an infringement on?) the rules of Christian temperance.

Two Galenic issues give the commentators the opportunity to refer to juridical and everyday life. The first is the discussion of hernias (of the omentum, intestinal: ἐπιπλοκήλη, ἐντεροκήλη). Fuchs, like Galen, explains the term vinculum (hindrance), the vinculum of the genitals as trouble of fertility (men are "unable to send forth the sperm directly"). But he does not limit himself to the merely medical aspect: his concern is about adoption as a juridical process. He distinguishes spadones, who are allowed to adopt because they can have children if healed, and castrati who are not allowed. The Latin jurists (Ulpian) use the term spado for all, castrati, thilbiae and eunuchs, which is an evidence of their ignorance, because, from a medical point of view, the cases are different. Greek juridical texts are of great help in order to re-establish adoption rules. Adoption is not the point in Galen.

The excretion process (evacuation of the superfluities, περιττώματα) produces different kinds of wind (7,(241)(242). If the physician is "perspicacious" and is well practiced in hearing, the sound produced by the wind shows the way of the περίττωμα through the body, which is useful for diagnosis: the sound can be a gurgling; it can also be "impure", like the one of the τυμβαῦλαι, the funeral musicians. Valleriole comments on those sounds, both of them connected with everyday people, everyday life: gurgling has a comic effect, underlined by the reference to Plautus' Olympio (called "Parasitus" by Valleriole), whose "inside is grumbling with emptiness". The "impure sound" is also produced by "our music instruments with the Greek name tymbala" (sic for cymbals). Their sound is "obscure but loud"; the plebeians in Valleriole's native city, Montpellier (plebei apud Monspessulum) play this music, accompanied by flute, when they perform (street) choral songs and dances (choreas et saltationes). There is no criticism against those performances, only a slightly condescending connotation of the word plebei.

Conclusion

The translations and commentaries of Galen in the Renaissance are first of all pieces of erudition, witnesses of a period of linguistic and educational concerns not only in the field of medicine, but also in the field of ideas. The translators and commentators rediscovered and adapted Galen, acting as mediators, as amatores of the veritas, aiming for a development of critical thinking in reading ancient sources. They are conscious that personal approach of those sources is indispensable for further reading and comprehension, and encourage students and learners not to limit themselves to the mere role of followers. Their criticism (somewhat vehement) of the Medieval, including the Arabic, tradition evidences that studying ancient knowledge was also an effort for or a process of emancipation.

However, translations and commentaries are not merely witnesses of an epoch or of learned milieus. Tone switching from medical to social and moral concerns shows that the Renaissance humanists wanted to take part in debates, beyond diagnosis, prognosis, and therapy. Reading those commentaries shows that medical "art" is not neutral, it can be controversial: medical precepts promote ideas, concepts, and practices. As far as I am concerned, it would not be anachronistic to consider that those precepts put forward by humanists can be regarded as current nowadays. Medicine and society are always in dialogue. That is why I think that the physician-learned man of yesterday and the physician-technician of the present day have much to exchange, and to benefit from each other.

Dina Bacalexi

Louis García-Ballester, "The new Galen: q challenge to Latin Galenism in thirteenth-century Montpellier", in Text and tradition, studies presented to Jutta Kollesch, ed. By K.-D. Fischer, D. Nickel, P.Porter, 1998, 55-83.