Francesco Chinello

Member, IEEE Claudio Pacchierotti

Member, IEEE Joao Bimbo

Senior Member, IEEE Nikos G Tsagarakis

Fellow, IEEE Domenico Prattichizzo

Design and evaluation of a wearable skin stretch device for haptic guidance

We present a wearable skin stretch device for the forearm. It is composed of four cylindrical end effectors, evenly distributed around the user's forearm. They can generate independent skin stretch stimuli at the palmar, dorsal, ulnar, and radial sides of the arm. When the four end effectors rotate in the same direction, the wearable device provides cutaneous stimuli about a desired pronation/supination of the forearm. On the other hand, when two opposite end effectors rotate in different directions, the cutaneous device provides cutaneous stimuli about a desired translation of the forearm. To evaluate the effectiveness of our device in providing navigation information, we carried out two experiments of haptic navigation. In the first one, subjects were asked to translate and rotate the forearm toward a target position and orientation, respectively. In the second experiment, subjects were asked to control a 6-DoF robotic manipulator to grasp and lift a target object. Haptic feedback provided by our wearable device improved the performance of both experiments with respect to providing no haptic feedback. Moreover, it showed similar performance with respect to sensory substitution via visual feedback, without overloading the visual channel.

I. INTRODUCTION

Haptic devices capable of providing only cutaneous stimuli have recently gained a great deal of attention in the haptics and robotics research fields. Cutaneous feedback provides an effective way to simplify the design of haptic interfaces [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: taxonomy, review, and perspectives[END_REF], [START_REF] Chinello | A three revolute-revolute-spherical wearable fingertip cutaneous device for stiffness rendering[END_REF], and it has been proven to play a key role in enhancing the performance and effectiveness of telepresence and immersive systems [START_REF] Pacchierotti | Cutaneous haptic feedback in robotic teleoperation[END_REF]- [START_REF]Augmentation of stiffness perception with a 1-degree-of-freedom skin stretch device[END_REF]. It is also particularly promising for robotic teleoperation applications, as cutaneous stimuli do not affect the stability and safety of the control loop [START_REF] Pacchierotti | Cutaneous haptic feedback in robotic teleoperation[END_REF], [START_REF]Augmentation of stiffness perception with a 1-degree-of-freedom skin stretch device[END_REF]- [START_REF] Pacchierotti | Cutaneous haptic feedback to ensure the stability of robotic teleoperation systems[END_REF], and navigation applications, as cutaneous stimuli can provide rich information in an unobtrusive and private way.

Indeed, several researchers have developed and used cutaneous devices for navigation purposes. Spiers et al. [START_REF] Spiers | Design and evaluation of shape-changing haptic interfaces for pedestrian navigation assistance[END_REF] designed a shape-changing handheld device to provide pedestrian navigation instructions. The device resembled a cube with an upper half that rotates and translates with F. Chinello is with the Dept. Business Development and Technology at Aarhus University in Herning, Midtjylland, Denmark. E-mail: chinello@btech.au.dk C. Pacchierotti is with the CNRS at Irisa and Inria Rennes Bretagne Atlantique, Rennes, France. E-mail: claudio.pacchierotti@irisa.fr.

J. Bimbo, N. G. Tsagarakis, and D. Prattichizzo are with the Dept. Advanced Robotics, Fondazione Istituto Italiano di Tecnologia, Genova, Italy. E-mail: {nikos.tsagarakis, domenico.prattichizzo}@iit.it D. Prattichizzo is also with the Dept. Information Engineering and Mathematics, University of Siena, Siena, Italy.

This research received funding from the EU Seventh Framework Programme FP7/2007-2013 under grant n ○ 601165 of the project "WEARHAP -WEARable HAPtics for humans and robots," and from Rennes Métropole under the "Allocation d'Installation Scientifique (AIS) 2017" programme. respect to the bottom half, that is grounded in the user's hand when held. The pose actuated by the device's upper half corresponds to heading and proximity to the target. Similarly, Imamura et al. [START_REF] Imamura | Hapmap: Haptic walking navigation system with support by the sense of handrail[END_REF] described a shape-changing handrail to guide users in unknown environments, and Hemmert [START_REF] Hemmert | Shapechanging mobiles: tapering in two-dimensional deformational displays in mobile phones[END_REF] presented a shape-changing mobile phone that moves its back cover to point the user toward the target. In addition to shape-changing devices, there is also an increasing interest in vibrotactile cutaneous feedback. The compact and lightweight form factor of vibrotactile motors has in fact enabled researchers to design highly wearable and portable vibrotactile interfaces. For example, Oron-Gilad [START_REF] Oron-Gilad | Vibrotactile guidance cues for target acquisition[END_REF] used two vibrotactile motors on the hand to convey directional information. The motors were placed either on the palm or on the back of the hand. Results found no differences between the two configurations. However, placing the motors on the back of the hand was preferred to avoid any impairment when grasping objects. More recently, a similar force illusion has been used by Rekimoto [START_REF] Rekimoto | Traxion: a tactile interaction device with virtual force sensation[END_REF] for pedestrian guiding systems. Another group of cutaneous devices providing navigation information uses skin stretch stimuli. These devices exploit the high sensitivity of human skin to tangential stretches and can provide the human user with rich directional information. Gleeson et al. [START_REF] Gleeson | Design of a fingertip-mounted tactile display with tangential skin displacement feedback[END_REF], for example, introduced a two-degreesof-freedom (2-DoF) skin stretch device for the fingertip. It laterally stretches the finger pulp using a 7 mm hemispherical tactor. Two RC servo motors and a compliant flexure stage can move the tactor in the plane of the finger pad.

However, the hand is not the only place where we can provide effective haptic guidance stimuli. One of the main reasons to move away from the hand is to enable a more direct and natural interaction with the surrounding environment. For example, this is particularly relevant in haptic-enabled Augmented Reality scenarios [START_REF] Maisto | Evaluation of wearable haptic systems for the fingers in augmented reality applications[END_REF], where users are asked to interact with virtual and real objects mixed together. But this is also relevant for navigation applications, where the aim is to provide effective and private navigation information to the users without impairing their motion and capability to interact with the environment. For these reasons, even though the hand is often regarded as a good location to convey haptic stimuli, it is common to find cutaneous devices that provide stimuli to other parts of the body. In this respect, the forearm has been often deemed as an effective placement to provide haptic guidance without impairing the user's hand. For example, Stanley and Kuchenbecker [START_REF] Stanley | Evaluation of tactile feedback methods for wrist rotation guidance[END_REF] tested five different cutaneous devices in wrist rotation guidance tasks. They were able to provide ten different forms of tactile feedback. Repeatedly tapping on the users' wrist on the side towards which they should turn showed the best performance. Rotella et al. [START_REF] Rotella | Hapi bands: a haptic augmented posture interface[END_REF] developed five haptic bands to be worn on the arms and wrists. They were instrumented with eccentric mass motors providing vibrotactile feedback for guidance of static poses. More recently, Yem et al. [START_REF] Yem | Development of wearable outercovering haptic display using ball effector for hand motion guidance[END_REF] presented a haptic display for hand guidance. This wearable outer-covering device is composed of two spherical end effectors that provide guidance information about the wrist's rotation and translation.

In this work, we present a novel cutaneous haptic device that provides navigation cues to the forearm in the form of lateral skin stretch haptic feedback, shown in Figs. 1. Four cylindrical rotating end effectors, located on the user's forearm, can generate skin stretch at the ulnar, radial, palmar, and dorsal sides of the arm. When all the end effectors rotate in the same direction, the cutaneous device is able to provide cues about a desired pronation/supination of the forearm (see Figs. 2a and2b). On the other hand, when two opposite end effectors rotate in opposite directions, the device is able to provide cutaneous cues about a desired translation of the forearm (see Figs. 2c and2d). Combining these two stimuli, we can provide both rotation and translation guidance to the forearm. With respect to other systems presented in the literature [START_REF] Rotella | Hapi bands: a haptic augmented posture interface[END_REF]- [START_REF] Kuniyasu | Transmission of forearm motion by tangential deformation of the skin[END_REF], this device is extremely wearable and unobtrusive [START_REF] Pacchierotti | Wearable haptic systems for the fingertip and the hand: taxonomy, review, and perspectives[END_REF]. Moreover, with respect to [START_REF] Spiers | Design and evaluation of shape-changing haptic interfaces for pedestrian navigation assistance[END_REF], [START_REF] Amemiya | Orienting kinesthetically: A haptic handheld wayfinder for people with visual impairments[END_REF], [START_REF] Koslover | Mobile navigation using haptic, audio, and visual direction cues with a handheld test platform[END_REF], it does not impair the hand. It weights 95 g, it adds 2.5 cm to the wrist size, and it is wireless. Moreover, with respect to other forearm solutions [START_REF] Stanley | Evaluation of tactile feedback methods for wrist rotation guidance[END_REF], [START_REF] Kuniyasu | Transmission of forearm motion by tangential deformation of the skin[END_REF], [START_REF] Nakamura | Development of a wrist-twisting haptic display using the hanger reflex[END_REF], it can provide information about both the rotation and translation of the wrist. A separate arm band, weighting 280 g, provides the required power and electronics. A preliminary version of this device has been presented in [START_REF] Chinello | Design of a wearable skin stretch cutaneous device for the upper limb[END_REF].

II. THE WEARABLE SKIN STRETCH DEVICE

The proposed wearable skin stretch cutaneous device is sketched in Fig. 1b, while a prototype is shown in Figs. 1a and1c. It is composed of four cylindrical end effectors (indicated as "C" in Figs. 1b and1c), that accommodate four Hitec HS-40 servomotors (B), and eight ergonomic pads (A), one in the rear and one in the front of each end effector. The end effectors and the ergonomic pads are made of ABSPlus. To improve grip and reduce slippage while contacting the skin, the end effectors are covered with rubber. The bracelet is wired to an arm band on the upper arm, that hosts a Raspberry Pi Model B, an Arduino Mini, and two 2 Ah batteries. The arm band is in charge of providing the required power to the device and manage the wireless communication between the device and an external computer. The cutaneous device weights 95 g while the arm band equipped with the batteries and control system weights 280 g. If no slip occurs, the movement of one of the end effectors onto the skin ∆S directly results in the same amount of skin stretch. This movement can be calculated as

∆S = ∆θ p ⋅ r, (1)
where r = 20 mm is the end effector radius (see Fig. 3), and ∆θ p is the commanded angle motion in radians.

To maximize the comfort and effectiveness of the haptic device, we placed it 10 cm proximal to the lunate bone (i.e., near the wrist) and fasten it until the end effector applied a force of 4 N normal to the skin. More details about this choice can be found in [START_REF] Chinello | Design of a wearable skin stretch cutaneous device for the upper limb[END_REF].

III. EXPERIMENTAL EVALUATION

To evaluate the effectiveness of our device in providing informative skin stretch sensations, we carried out two experiments of haptic navigation.

A. Experiment #1: preliminary arm guidance

In the first experiment, we aim at evaluating the guiding capabilities of our device in a simple wrist navigation task.

1) Experimental setup and task:

The experimental setup is composed of our wearable skin stretch device, as shown in Fig. 1. The force applied on the forearm skin was registered at the beginning of the experiment using four piezoresistive Force Sensing Resistor (FSR) sensors placed between the end effectors and the forearm. The FSR sensors were then removed to enable the subject to carry out the tasks. At the end of the experiment, the sensors were re-positioned to register any significant change in the fastening force. The maximum reduction of fastening force we registered was 0.6 N, which we found acceptable. No subject reported any significant change in the fastening force or in the positioning of the device.

To detect pronation, supination, and translation of the forearm, we used a Leap Motion tracker.

The task consisted of rotating or translating the forearm following the navigation cues provided by the skin stretch device, being as accurate as possible. A video of the experiment is available as supplemental material. To avoid external distractions, subjects wore noise-canceling headphones and were blindfolded. Reference rotations and translations were 2) Subjects and methods: Ten participants were involved in this first experiment, including three women and seven men. Seven participants had previous experience with haptic interfaces. Before starting the task, the experimenter explained the procedure and spent about two minutes adjusting the setup to be comfortable. One practice trial was allowed.

Each subject carried out thirty-six randomized trials of the navigation task, with twelve repetitions for each feedback condition:

• navigation feedback regarding the desired rotation/translation of the forearm using our wearable skin stretch device (condition CF),

• navigation feedback regarding the desired rotation/translation of the forearm using visual cues (condition V),

• no navigation feedback (condition N), In the first condition CF, the wearable device provides haptic navigation feedback about pronation, supination, and translation of the forearm, as detailed in Sec. II and shown in Fig. 2. Subjects should thus rotate/translate their forearm following the cutaneous information provided by the device. The closer the subject is to the target orientation/position of the forearm, the less stretch the device applies to the skin. When the subject reaches the desired orientation/position, the device applies no skin stretch to the forearm. Another viable control policy would have been to directly provide the target hand pose, so that subjects would have had to try maintaining a constant skin stretch. However, applying a constant stretch stimulus for a long period results in a reduced sensation [START_REF] Burgess | Cutaneous mechanoreceptors and nociceptors[END_REF]. For this reason, we decided to provide information about the error between the current and target hand poses. To avoid slippage and achieve the highest accuracy, the cutaneous device maps the target rotation/translation to a skin stretch in the [-8.75, 8.75] mm range, corresponding to a pulley rotation in the θ p ∈ [-25, 25] ○ range [START_REF] Chinello | Design of a wearable skin stretch cutaneous device for the upper limb[END_REF]. This proportional control policy for controlling the device rotations and translation during the experiment is summarized by the two algorithms below.

Algorithm 1: Skin stretch control policy for rotations set target rotation θ r foreach time step do measure current rotation θ m

θ p = 25 (θ r -θ m ) θ r .
if θ p > 25 then θ p = sgn(θ p )25. end apply rotation θ p to all the pulleys (see Fig. 2). exit when subject feels to be at the right orientation. end if θ p > 25 then θ p = sgn(θ p )25. end apply rotations ±θ p to two opposite pulleys, according to the target direction of motion (see Fig. 2). exit when subject feels to be at the right position. end

In condition V, no cutaneous feedback is provided to the subjects. An LCD screen is placed in front of them and an arrow indicates the target direction or orientation. The length of the arrow indicates how far the subject is from the target direction or orientation. In condition N, neither cutaneous nor visual feedback is provided to the subjects. At the beginning of the task, the experimenter communicates the target movement to the subject.

The ten participants carried out twelve repetitions of the navigation task in each feedback condition, two times for each navigation modality: pronation (Fig. 2a), supination (Fig. 2b), translation to the right (Fig. 2d), translation to the left, elevation (Fig. 2c), and lowering of the forearm.

3) Results: Rotation and position errors as well as completion time provided a measure of performance. Low values for these metrics indicate the best performance.

Fig. 4a shows the average absolute rotation error at the end of the task. All the data passed the Shapiro-Wilk normality test and Mauchly's Test of Sphericity. A one-way repeatedmeasures ANOVA test showed statistically significant changes between the feedback conditions (F(2, 18) = 35.351, p < 0.001). Post-hoc analysis with Bonferroni correction showed statistically significant differences between CF vs. N with p < 0.001 and V vs. N with p = 0.001. Fig. 4b shows the average absolute translation error at the end of the task for each condition. All the data passed the Shapiro-Wilk normality test. Mauchly's Test of Sphericity indicated that the assumption of sphericity was violated (χ 2 = 22.286, p < 0.001). A one-way repeated-measures ANOVA test with a Greenhouse-Geisser correction showed statistically significant changes between the feedback conditions (F(1.016, 9.141) = 13.267, p < 0.001). The Greenhouse-Geisser correction is used when the assumptions of sphericity or equal variances are violated, as in this case. It corrects the analysis by calculating new degrees of freedom and a new significance value p, so that a valid F-ratio can be obtained. Post-hoc analysis with Bonferroni correction showed statistically significant differences between all conditions: CF vs. V, p = 0.032; CF vs. N, p = 0.020; and V vs. N, p = 0.016. Finally, we also measured the completion time. All the data passed the Shapiro-Wilk normality test and Mauchly's Test of Sphericity. A one-way repeated-measures ANOVA indicated no significant difference in the performance among feedback conditions. Average completion time was 5.06 ± 1.02 s (mean ± SD). Immediately after the experiment, subjects were also asked to choose the condition they preferred the most. Condition CF was preferred by two subjects, while condition V was preferred by eight subjects.

B. Experiment #2: robotic telemanipulation

In the second experiment, we aim at evaluating the guiding capabilities of our device in a robotic telemanipulation task.

1) Experimental setup and task:

The experimental setup and remote environment are shown in Fig. 5. The master side is composed of our skin stretch device, as shown in Fig. 1. Moreover, a Leap Motion tracker is in charge of registering the position, orientation, and grasping configuration of the operator's hand. The hand grasping configuration, i.e., how closed the hand is, is measured by considering the radian angle g h between the index finger's distal phalanx direction ĥf and the hand direction ĥw (see Fig. 1a and [START_REF] Bimbo | Teleoperation in cluttered environments with distributed wearable haptic feedback[END_REF]),

g h = cos -1 ĥf ⋅ ĥw . (2)
The slave robot is composed of the anthropomorphic Pisa/IIT SoftHand soft robotic hand, attached to a 6-DoF Universal Robot 5 manipulator (Universal Robots A/S, Denmark). A small camera is attached to the robot's wrist, showing the environment in front of the robotic hand. The SoftHand uses only one actuator to activate its adaptive synergy [START_REF] Catalano | Adaptive synergies for the design and control of the pisa/iit softhand[END_REF]. The index, middle, ring, and little fingers have four phalanges, while the thumb has three. The hand is connected to a flange, to be fixed at the manipulator's end effector, through a compliant wrist allowing for three passively compliant degrees of freedom. The motor of the hand is driven by commanding a grasping variable g r ∈ [0, 1], which sets the hand closure. The 6-DoF manipulator is able to move the end effector at up to 1 m/s and each joint at 180 deg/s. Its repeatability is ±0.1 mm for quick-precision handling with a maximum payload of 5 kg [START_REF] Ostergaard | Lightweight robot for everybody [industrial activities[END_REF].

The desired pose of the robotic hand and wrist at time t, B T D (t), is commanded using a mapping between the Soft-Hand and the user's hand, tracked by the Leap Motion [START_REF] Bimbo | Teleoperation in cluttered environments with distributed wearable haptic feedback[END_REF]. The keyboard works as a clutch. All coordinate frames but the one on the robot base B are shown in Figs. 5 and6. Frame B has its origin on the robot base, with the z axis orthogonal to the table (pointing up), the x axis parallel to the table (pointing toward the obstacle), and the y consequently defined. When the space key is pressed, the current pose of the user's hand with respect to the Leap Motion base L T H ∈ SE(3) and the robot's end effector pose with respect to its base B T E are saved:

L T H (0) = L T H (t) B T E (0) = B T E (t).
As the user moves his hand, the desired end effector pose is calculated according to eq. ( 3), using the poses saved when the user started pressing the clutch, such that their relative motions are equal, i.e., E0 T D = H0 T H ,

B T D (t) = B T E (0) ⋅ L T -1 H (0) ⋅ L T H (t). (3)
This mapping allows the robot to be commanded in a natural way while looking at the camera: if the user moves his hand in the z direction of the H frame, the robot will move along the z direction of its frame E. This approach also allows the user to start the motion with the hand at an arbitrary position with respect to the Leap Motion, enabling the user to also pause, move to a more comfortable or suitable position, and then resume the control of the robot.

To also match as closely as possible the grasping configuration of the operator's hand, we define the input commanded to the hand DC motor as g r = g h π -1 , where a command of 0% closure is sent when the index is parallel with the palm direction and 100% closure is commanded when the index finger is bent 180 ○ (see eq. ( 2) and Fig. 1a).

The remote environment is composed of the slave robot, an obstacle, and a target object to grasp (i.e., a bottle of water). The task consisted of moving the slave robot in the remote environment and picking up the target object, following the navigation information provided by the device and avoiding contacts with obstacles (see Fig. 5). A video of the experiment is available as supplemental material.

2) Subjects and Methods: Ten participants took part in the experiment, including one women and nine men. Six of them had previous experience with haptic interfaces. Before starting the experiment, the experimenter explained the procedure and spent about three minutes adjusting the setup to be comfortable. One practice trial was allowed.

We considered two different trajectories (t r vs. t p ), two different orientations of the target object to grasp (o d vs. o u ), and three different haptic feedback conditions (CF vs. V vs. N), ending up with 2 (trajectories) × 2 (object orientations) × 3 (feedbacks) = 12 different experimental conditions. The two trajectories are shown in Fig. 6. The first trajectory moves the robot following a rectangular shape around the obstacle (t r ), while the second one moves the robot following a parabolic shape around the obstacle (t p ). The water bottle to grasp can be either standing (o u ) or laying (o d ) on the table. The configuration of the bottle on the table also defines the final target orientation for the robotic hand with respect to the B frame, chosen to enable a successful grasp: γ = rot(x) B = 0 ○ for o d (hand palm parallel to the table) and γ = rot(x) B = 90 ○ for o u (hand palm perpendicular to the table), i.e., with the palm parallel to the bottle. The starting position and orientation of the hand are chosen randomly around the first point of the trajectory, as shown in Fig. 6. Finally, the human operator receives navigation feedback about the desired trajectory and orientation through our skin stretch device (CF), through sensory substitution via visual feedback (V), or receive no feedback at all (N).

Each trajectory is divided into 60 equidistant points (green squares in Fig. 6). Given the hand position, the current target point is defined as the point along the trajectory which comes next after the one closest to the robotic hand (red square in Fig. 6). All the points except the last one commands a target orientation of rot(x) B = 0. The target orientation for the last point depends on the bottle configuration, as specified above. The control policy for this experiment is summarized in the In condition CF, our wearable cutaneous device provides the subject with navigation information about the translation and orientation of the robotic hand. Similarly to Sec. III-A, the more the subject rotates/translates the forearm toward the target point of the trajectory, the less stretch the device applies to the skin. As before, to avoid slippage and provide the highest accuracy, the cutaneous device always maps the target rotation/translation to a skin stretch in the range [-8.75, 8.75] mm. Once the target position and orientation is defined as per Algorithm 3, skin stretch stimuli are provided to the human operator combining the control policies detailed in Algorithms 1 and 2. In condition V, no cutaneous feedback is provided to the subjects. An arrow, superimposed on the camera view of the remote environment, indicates the target direction and orientation of the robotic hand. As for Sec. III-A, the length of the arrow indicates how far the subject is from the target direction or orientation. In condition N, no navigation feedback is provided to the subjects. Before the beginning of the task, the experimenter shows the subject a picture of the target trajectory and orientation superimposed to the environment, e.g., Fig. 6a or Fig. 6b. The operator has then to rely only on the visual information provided by the camera to complete the grasping task. Subjects performed twenty-four repetitions of the navigation task, two for each experimental condition.

3) Results: Translation error, orientation error, and outcome of the task were measures of performance. Fig. 7a shows the average absolute orientation error, calculated as the RMS of the difference in orientation between the robotic hand and the target orientation during the task. All the data passed the Shapiro-Wilk normality test and Mauchly's Test of Sphericity. A one-way repeated-measures ANOVA test revealed statistically significant changes between the feedback conditions (F(2, 18) = 24.408, p < 0.001). Posthoc analysis with Bonferroni correction revealed statistically significant difference between CF vs. N with p = 0.003 and V vs. N with p = 0.001. Fig. 7b shows the average absolute translation error, calculated as the RMS of the distance between the robotic hand and the target trajectory during the task. All the data passed the Shapiro-Wilk normality test. Mauchly's Test of Sphericity indicated that the assumption of sphericity had been violated (χ 2 = 22.450, p < 0.001). A one-way repeated-measures ANOVA test with a Greenhouse-Geisser correction revealed statistically significant changes between the feedback conditions (F(1.031, 9.280) = 25.387, p = 0.001). Post-hoc analysis with Bonferroni correction revealed statistically significant difference between conditions CF vs. N, p = 0.002; and V vs. N, p = 0.002. Fig. 7c shows the average success rate of the task. A task was considered successfully completed when the slave robot was able to grasp the bottle and lift it from the ground. A Friedman test showed a statistically significant difference between the means of the feedback conditions (χ 2 (2) = 8.909, p = 0.012). Post hoc analysis with Bonferroni correction revealed a statistically significant difference between conditions CF vs. N (p = 0.002) 7. Experiment #2. RMS orientation and position error, success rate, and perceived effectiveness provided a measure of performance for conditions CF (in blue), V (in red), and N (in green). Mean and 95% confidence interval are plotted. and V vs. N (p = 0.004). The failures were due to too high collisions forces between the robot and the obstacle, which caused the manipulator to go into protective mode. We also measured the completion time. All the data passed the Shapiro-Wilk normality test and Mauchly's Test of Sphericity. A one-way repeated-measures ANOVA indicated no significant difference in the performance among feedback conditions. Average completion time was 168.93 ± 10.52 s (mean ± SD). We also tested whether the task completion time affected the task performance. hypothesis is that subjects who took more time were able to also achieve higher performance in the considered metrics. A Pearson's product-moment correlation was run to assess the relationship between this distance and the error in following the desired trajectory with the gripper. A preliminary analysis showed that the relationship was with normally distributed variable, according to the Shapiro-Wilk test, and there were no outliers. There was a strong positive correlation between the completion time vs. rotation error (r(x) = 0.750, p < 0.001) and translation error (r(x) = 0.880, p < 0.001), confirming our hypothesis.

Besides this evaluation, we also assessed the users' experience. Immediately after the experiment, subjects were asked to complete a questionaire that used bipolar Likerttype eleven-point scales, reporting the effectiveness of each feedback condition in completing the given task. Figure 7d shows the perceived effectiveness of the three feedback conditions. A Friedman test showed a statistically significant difference between the means of the feedback conditions (χ 2 (2) = 16.270, p < 0.001). Post hoc analysis with Bonferroni revealed a statistically significant difference between conditions CF vs. N (p = 0.002) and V vs. N (p = 0.004). Finally, subjects were also asked to choose the condition they preferred the most. Condition CF was preferred by five subjects and condition V was preferred by five subjects. No subject reported any significant change in the fastening force or in the positioning of the device during the task.

IV. DISCUSSION AND CONCLUSIONS

In this paper we presented a wearable cutaneous device able to provide navigation cues through lateral skin stretch haptic feedback. The device is shown in Figs. 1. Four rotating end effectors with cylindrical shape can generate skin stretches independently at the ulnar, radial, palmar, and dorsal sides of a user's forearm. When the end effectors all rotate in the same direction, the device provides cutaneous cues about a desired pronation/supination of the forearm. When two opposite end effectors rotate in opposite directions, the device provides cutaneous cues about a desired translation of the forearm. The device weights 95 g, it adds only 2.5 cm to the wrist size, and it is wireless. A separate arm band, weighting 280 g, provides the required power and electronics.

We carried out two experiments of haptic navigation, enrolling a total of 20 subjects. In the first experiment, subjects had to translate and rotate the forearm toward a target position and orientation, respectively. Our haptic device (CF) and sensory substitution with visual feedback (V) significantly improved the performance of the task with respect to providing no navigation feedback (N). Sensory substitution with visual feedback outperformed cutaneous feedback in one metric. Finally, most subjects preferred visual feedback over cutaneous feedback, as they found the visual information more natural and requiring less concentration with respect to the cutaneous one. Nonetheless, this large difference in preference (8 vs. 2 subjects for condition V) did not reflect the task performance. In fact, a significant lower error of condition V vs. condition CF was found only for the translation metric (see Fig. 4b), while in the rotation metric condition CF performed even better than condition V (although no statistically significant difference was found, see Fig. 4a).

In the second experiment, subjects were asked to control the motion and orientation of a 6-DoF robotic manipulator to grasp and lift a target object. Conversely to Experiment #1, this time condition CF was more appreciated by the subjects, who considered it as effective as visual feedback. However, subjects again reported the visual condition to be more natural with respect to the cutaneous one. Nonetheless, 9 subjects out of 10 reported that in condition V it was hard to concentrate, at the same time, on the arrow indicating the target hand pose and on the camera view of the remote environment (see top of Fig. 5a). In this respect, providing navigation information through the skin stretch device prevented an overload of the visual channel. Similar results have been demonstrated also for other teleoperation applications, where providing cutaneous feedback outperformed sensory substitution via visual cues [START_REF] Pacchierotti | Cutaneous feedback of fingertip deformation and vibration for palpation in robotic surgery[END_REF]- [START_REF] Pacchierotti | Teleoperation of steerable flexible needles by combining kinesthetic and vibratory feedback[END_REF]. Results also showed that cutaneous feedback and sensory substitution with visual feedback significantly improved the performance of the task with respect to providing no navigation feedback. No significant difference was found between conditions CF and V.

Our skin stretch device was proven to be a viable solution for navigation feedback in human guidance and robotic telemanipulation systems. However, haptic guidance was still found to be less natural to follow than visual guidance. In this respect, we should take into account that we are used everyday to follow visual navigation cues (e.g., turn-by-turn car navigation systems, road signs), while we are not used to follow haptic navigation stimuli at all. In this respect, we expect more training to improve the performance of the haptic modality. Moreover, while visual cues may be superior when there are no other cues to follow, whenever the operator receives more than one information flow through the visual providing haptic feedback seems a very good option. This is a common situation in robotic teleoperation, where the human operator looks at the camera visual stream and, at the same time, is provided with additional information about the forces exerted by the slave robot, a predetermined trajectory to follow, or the presence of surrounding obstacles. While these pieces of can be superimposed on the screen, as we have done in condition V of Experiment #2, our results show that using haptic feedback can provide comparable performance without overloading the visual channel -proving cutaneous feedback to be the best choice.

In the future, we plan to run more experiments to study how the performance and subjects' preference change after some training. We also plan to test the effect of providing navigation information using visual and skin stretch cues together. Finally, we also plan to run a longer evaluation session, in order to understand if the current fasting mechanism is capable of keeping the device in place during a prolonged use.

Fig. 1 .

 1 Fig. 1. Prototype of the wearable skin stretch cutaneous device. Four cylindrical end effectors provide independent skin stretch stimuli at the palmar, dorsal, ulnar, and radial sides of the arm. It is composed of the four cylindrical end effectors (C), that accommodate four servomotors (B), and eight ergonomic pads (A), one in the rear and one in the front of each end effector.

Fig. 2 .

 2 Fig.2. Working principle. When the four end effectors rotate in the same direction, the wearable device conveys cutaneous feedback about a desired pronation/supination of the forearm (see (a) and (b)). On the other hand, when two opposite end effectors rotate in opposite directions, the device conveys cutaneous feedback about a desired translation of the forearm (see (c) and (d)).

Fig. 3 .

 3 Fig.3. Kinematic scheme of one skin stretch module. The proposed wearable device is composed of four skin stretch modules.

Fig. 4 .

 4 Fig.[START_REF] Quek | Sensory augmentation of stiffness using fingerpad skin stretch[END_REF]. Experiment #1. Subjects were asked to rotate/translate the forearm following the navigation information provided by the device, being as accurate as possible. Absolute orientation and position error provided a measure of performance. Mean and 95% confidence interval are plotted.

Algorithm 2 :

 2 Skin stretch control policy for translations set target translation d r foreach time step do measure current translation d m θ p = 25 (d rd m ) d r .

  (a) Master side. (b) Slave side.

Fig. 5 .

 5 Fig. 5. Experiment #2. The master system is composed of the wearable skin stretch device and a Leap Motion controller. The slave system is composed of the Pisa/IIT SoftHand soft robotic hand attached to the end effector of a 6-DoF Universal Robot 5 manipulator. A camera attached to the robot's wrist shows the remote environment to the human operator. The desired pose and grasping configuration of the robotic hand are controlled by the human operator as detailed in Sec. III-B.1. The keyboard works as a clutch.

Fig. 6 .

 6 Fig.6. Experiment #2. The task consisted of moving the slave robot in the remote environment and picking up the plastic bottle, following the navigation information provided by the device and avoiding contacts with obstacles. A video of the experiment is available as supplemental material.

  Fig.7. Experiment #2. RMS orientation and position error, success rate, and perceived effectiveness provided a measure of performance for conditions CF (in blue), V (in red), and N (in green). Mean and 95% confidence interval are plotted.


Filippo Sanfilippo
email: filippo.sanfilippo@usn.no

Claudio Pacchierotti

Paper-A Wearable Haptic System for the Health Monitoring of Elderly People in Smart Cities A Wearable Haptic System for the Health Monitoring of Elderly People in Smart Cities

Keywords: sensor fusion, wearable, health monitoring, elderly !

A sensor-fusion wearable health-monitoring system with integrated haptic feedback was previously introduced by our research group. The system's components are the following: a chest-worn device with an embedded controller board, an electrocardiogram (ECG) sensor, a temperature sensor, an accelerometer, a vibration motor, a colour-changing light-emitting diode (LED) and a push-button. This multi-sensor device makes possible to collect biometric and medical monitoring data from its wearer. The data provide a real-time indication of the wearer's health state and can also be further analysed later for medical diagnosis. The embedded vibration motor can actuate distinctive haptic feedback patterns according to the wearer's health state. The embedded colourchanging LED provides the wearer with an additional intuitive visual feedback of the current health state, and the wearer can report a potential emergency condition by using the push-button. In this paper, a conceptual case study is presented concerning possible applications for the health monitoring of elderly people in smart cities. The proposed system aims at reducing risk by assessing individual and overall potentially-harmful situations. A data collection and analysis are also presented to demonstrate that the system can provide compelling vibrotactile feedback.

Introduction

Several large technology companies including Apple, Google, and Samsung are entering the expanding market of population health monitoring with the introduction of wearable devices, also known as "wearables". These devices are now at the heart of just about every discussion related to the Internet of Things (IoT) and the full range of new capabilities pervasive connectivity can bring [START_REF] Swan | Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0[END_REF] to smart cities and health monitoring applications. Wearability of smart devices is envisioned to enable novel forms of interaction, communication, cooperation and integration between humans and automated information systems. Specifically, wearables make it possible to provide haptic feedback to the human wearer during natural interaction with the environment. Haptic feedback, also known as haptics, is the use of the sense of touch in a user interface designed to supply the user with additional information. For instance, specific vibrotactile feedback may provide the user with real-time feedback about its health status.

In this perspective, the design and development of wearable health-monitoring systems (WHMS) has received lots of attention from the scientific community and industry during the last years. These low-cost systems are made up of various small sensors, transmission modules and processors. As a result, they are well-suited to wearable and unobtrusive mental and physical health status monitoring solutions and do not impose limits on time or location [START_REF] Pantelopoulos | A survey on wearable sensor-based systems for health monitoring and prognosis[END_REF]. Even though independent sensor information is conducive to revealing the working state of the system to some extent, a comprehensive multi-parameter sensing model is more effective for analysis and evaluation of potential operational risks. To the best of our knowledge, multi-sensor fusion is one of the most suitable technologies to use when dealing with data from disparate sources [START_REF] Yang | Multi-sensor fusion[END_REF].

Following this approach, our research group previously present a wearable health sensor monitoring system based on a multi-sensor fusion approach [START_REF] Sanfilippo | A sensor fusion wearable health-monitoring system with haptic feedback[END_REF]. It consists of a chest-worn device that embeds a controller board, an electrocardiogram (ECG) sensor, a temperature sensor, an accelerometer, a vibration motor, a colour-changing light-emitting diode (LED) and a push-button. Biometric and medical monitoring applications can be performed by using this multi-sensor device. The embedded vibration motor makes it possible to actuate distinctive haptic feedback patterns according to the wearer's health state. In this way, the user can intuitively become self aware of his own health situation. The user is also provided with an additional intuitive visual feedback about the current health state by means of the embedded colour-changing LED. In addition, the provided push-button can be used by the user to report a potential emergency state. The proposed system opens up to a variety of application possibilities.

In this paper, we discuss the possibility of employing our system for the health monitoring of elderly people in smart cities, as shown in Figure 1. By collecting the sensor data, it is possible to monitor the health state of a user or to get sensitive data in real-time. Retrieved data can subsequently be analysed for medical diagnosis. Biometric information gathered can be wirelessly sent using the standard Wi-Fi communication protocol to a medical diagnosis center. Data can be sent to a cloud computing system to perform permanent storage or visualised in real-time by sending the information directly to a laptop or smart phone. Encryption techniques can be used to transfer data securely and to consider privacy concerns. Data mining can be performed with the raw data and could be used in conjunction with methods from the fields of artificial intelligence, machine learning, statistics and database systems by using a knowledge base. The overall goal of the data mining process is to extract information from the data set and transform it into an understandable structure so that it is possible to find previously unknown information to make inferences regarding the user's health state. In the context of constantly aging populations, maintaining persons at home represents one of the most serious challenge to be considered. The proposed system may make it possible for elderly people to live longer in their own homes.

The paper is organised as follows. A review of the related research work is given in Sect. 2. In Sect. 3, the system architecture is presented. Some ethical issues are discussed in Sect. 4. A conceptual case study describing the health monitoring of elderly people in smart cities is presented in Sect. 5. Conclusions and future work are outlined in Sect. 6.

2

Related research works

In the last decade, there have been numerous research efforts and products that can be classified as WHMS [START_REF] Pantelopoulos | A survey on wearable sensor-based systems for health monitoring and prognosis[END_REF].

For example, Lv et al. [START_REF] Lv | icare: a mobile health monitoring system for the elderly[END_REF] developed a mobile health monitoring system for the elderly. They used wireless body sensors and smart phones to monitor the wellbeing of the elderly, controlling the position, blood pressure, and ECG signal of the wearer. Rajasekaran et al. [START_REF] Rajasekaran | Elderlypatient monitoring system using a wireless sensor network[END_REF] presented a network that supports wearable sensors and contains on-board general computing capabilities for individual event detection, alerts, and communications with different medical services. The information is relied in real time to the PDAs of the doctor and/or caretaker. The Smart Shirt from Sensatex [START_REF] Park | Thewearablemotherboard: a framework for personalized mobile information processing (pmip)[END_REF] is a wearable health-monitoring device that integrates a number of sensory devices, such as heart monitor, respiration, temperature, onto a wearable mother-board from Georgia Tech. Several other technologies have been also introduced, including the MIThril by MIT [START_REF] Martin | Towardsadesign framework for wearable electronic textiles[END_REF], e-textile from Carnegie Mellon University, and wearable e-textile from Virginia Tech [START_REF] Marculescu | Challenges and opportunities in electronic textiles modeling and optimization[END_REF]. Furthermore, the Lifeguard project of Stanford University is a physiological monitoring system comprising physiological sensors (ECG/respiration electrodes, pulse oximeter, blood pressure monitor, temperature probe), a wearable device with built-in accelerometers, and a base station. The crew physiologic observation device acquires and logs the physiological parameters measured by the sensors. More recently, Dong et al. [START_REF] Dong | The elderly health monitoring platform based on spark[END_REF] proposed an elderly health-monitoring distributed platform, which collects health data through intelligent wearable sensors and then send them to a remote server through a smartphone. Using big data technology and parallel computing, the platform uses Spark Streaming technology to carry out the online data stream processing, so as to feedback the results to the designated emergency center, hospital, or family.

Nonetheless, to the best of our knowledge, an health sensor monitoring system that features a multi-sensor fusion approach and also provides an integrated haptic feedback for the user has not yet been deeply investigated. The lack for such a system is even more evident when considering the rapidly growing needs of urban population in terms of health care. This challenge is one of the key driver for governments to increase digitization-acceleration efforts involving smart cities. The main contribution of this paper is to contribute towards the development of a wearable haptic healthmonitoring system based on sensor information fusion for the health monitoring of elderly people in smart cities.

System architecture

In this section, the proposed system architecture is presented. The framework is based on a multi-sensor fusion approach. In particular, a client-server pattern is adopted. A chest-worn device operates as a client and remotely communicates with a server where the logic of the presented architecture is implemented. In the following, the adopted design method is first described. Successively, the key elements of the system are presented. The reader is referred to Figure 2.

Design method

During the overall system design process, we adopted advanced virtual prototyping methods and simulations tools with the aim of improving our architectural choices, testing procedures and validation techniques. From a design point of view, virtual prototyping can be beneficial when developing complex systems. Development time can be significantly reduced, the system features can be extensively tested and quality can be assessed [START_REF] Wang | Definition and review of virtual prototyping[END_REF]. Therefore, virtual prototyping is necessary for validating the system design. Related simulations are carried out. In particular, this system allows for an effective risk reduction from both an individual assessment as well as an overall evaluation of the potential harm.

Client (chest-worn device)

The wearable device is designed to work as a client and gather different biometric data. In particular, it is a chest-worn device that consists of a controller box attached to a belt. The device is worn by the user and it is powered by means of a polymer lithium ion battery. In the following, the components that are housed in the controller box are listed:

• Controller board: an Arduino Uno board [START_REF] Arduino | Arduino, an open-source electronics prototyping platform[END_REF] based on the ATmega328 microcontroller is used as a client.

Arduino is an open-source electronics prototyping platform based on flexible, easy-to-use hardware and software. Using Arduino boards simplifies the amount of hardware and software development needed to get a system running. On the software side, Arduino provides a number of libraries to make programming the micro-controller easier. The choice of using Arduino boards makes the system framework easy to maintain and makes it possible to easily add new features in the future; • Communication module: to give communication capabilities to the proposed wearable device, an Arduino WiFi Shield [START_REF] Arduino | Arduino, an open-source electronics prototyping platform[END_REF] is stacked on top of the adopted controller board. In detail, the Arduino WiFi Shield allows the client to communicate with the server by using the 802.11 wireless specification (WiFi). The Arduino WiFi Shield connects to an Arduino Uno board using long wire-wrap headers that extend through the shield. This keeps the pin layout intact and allows another shield to be stacked on top; • Memory Shield Module: a Secure Digital (SD) card reader module and an SD memory card are adopted to locally store data through the Serial Peripheral Interface (SPI) by using the file system driver. This local memory is mainly used to store sensitive data such as the user's identity and other information that cannot be stored on the server side for privacy reasons. The local memory is also useful when no communication links are available. In this case, data are first temporary stored locally and then uploaded to the server whenever a connection link is available; • Sensor platform: to gather the wearer's biometric data, an e-Health Sensor Shield • Battery: a polymer lithium ion battery is adopted in order to provide power to the proposed controller box. This kind of battery is very slim and extremely light weight.

Different biometric sensors can be connected to the e-Health Sensor Shield according to various needs. Specifically, the following sensors are employed in our implementation:

• an ECG sensor kit, which consists of three leads (positive, negative and neutral) to be attached to the user's body. This sensor input can be used as a diagnostic tool to assess the electrical and muscular functions of the user's heart. The ECG has grown to be one of the most commonly used tests in modern medicine. In particular, this sensor has proven to be useful in the diagnosis of several cardiac pathologies ranging from myocardial ischemia and infarction to syncope and palpitations. However, the accuracy of the ECG depends on the condition being tested. A heart problem may not always show up on the ECG. Some heart conditions never produce any specific ECG changes [START_REF] Mcnames | Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes[END_REF]; • an accelerometer sensor, which can be placed on the user's body with a comfortable elastic band. This sensor can be used to monitor five different wearer positions (standing/sitting, supine, prone, left and right). In many cases, it is necessary to monitor the user's body positions and movements because of their connection to particular diseases (i.e., restless legs syndrome). For the particular case of elderly people, analysing movements during daily activities also helps in determining life quality and irregular pattern behaviours. The accelerometer sensor could also help to detect fainting or falling of the elderly people; • a temperature sensor, which can be placed under the user's axilla. Body temperature is an important health state indicator and accurate measurements can provide medical insight into the wearer's response to different situations. The reason is that a number of diseases are accompanied by characteristic changes in body temperature. Likewise, the course of certain diseases can be monitored by measuring body temperature, and the efficiency of a treatment can be evaluated by the physician.

Another relevant feature of the proposed wearable device is that it provides the wearer with an intuitive haptic and visual feedback. To implement this feature, the following components are adopted:

• a vibration motor is embedded in the proposed chest-worn device. The motor is placed on the back side of the controller box and it allows for actuating distinctive haptic feedback patterns according to the wearer's health state. This feature is fundamental for improving the user's risk perception. The way in which people think, feel and behave in response to risk is receiving increasing attention, both among academics and those who are involved in promoting and regulating safety. Risk is perceived differently by different people. In this perspective, the use of haptics can significantly improve the user experience. Touch is one of the most reliable and robust senses: it is fundamental to our memory and for discerning. When the wearer's health state is normal, the motor does not produce any vibrations. If instead, the wearer's health state is not normal, two different vibration patterns are actuated to symbolise a potentially abnormal condition (low frequency vibrations) or a rather dangerous state of health (high frequency vibrations); • a colour-changing LED is embedded in the proposed chest-worn device and placed on the visible side of the controller box. This LED provides the user with an additional intuitive visual feedback of the current health state. In particular, three different colours are used: green to indicate a normal health state, yellow to symbolise a potentially abnormal condition and red to point out a dangerous health state.

In addition, a push-button is embedded in the proposed wearable device, allowing the user to report a potential emergency condition or accident.

Multi-threading and multi-level hierarchical server

The server implements a multi-threading and multi-level control program. Strict real-time criteria are adopted. This allows to simultaneously and efficiently collect data from different users. Moreover, the chosen architectural pattern offers the following advantages: improved performance and concurrency; simplified coding of remote procedure calls and conversations; scalability and possibility to handle a growing number of users.

Three different logical levels are defined to process the client requests:

• the High-Level methods layer includes the high-level and distributed control function, processRequest, which handles each client request; • the Concurrent Threads level is the layer where each client request is treated as a concurrent process. In detail, the health state of each user is continuously monitored by a separate thread. This level can access both the lower Low-Level methods layer as well as the higher High-Level methods layer. Each monitoring thread continuously sends the current information status back to the corresponding client so that the vibration motor and the LED can be accordingly actuated; • the Low-Level methods layer includes the low-level functions that are used to write the acquired data to a local database (write), to read previously acquired data from a local database (read), to send the acquired data to the cloud (send), to receive previously acquired data from the cloud (receive), and to send data from the server to a knowledge base where the data can be analysed (analyse).

From an implementation point of view, the server is implemented by using the Java programming language and the corresponding standard tools for multi-threaded programming.

Knowledge Base

The proposed system can communicate with a knowledge base (KB). A KB may store complex structured and unstructured information collected from different sources such as public hospital databases and other health care facilities. KB technology and methods from the fields of artificial intelligence, machine learning, statistics and database systems can be employed to process the health measurement data and to look for unusual signs or trends.

In this initial study, the interface that provides the possibility of exposing data from the server side to an hypothetical KB was developed. In the future, rules for execution by an inference mechanism of an automation program may be implemented [START_REF] Pang | Health monitoring of elderly in independent and assisted living[END_REF]. The rules must be based on the expertise of the health professionals. The rules would describe the range values of the health data that requires constant monitoring. In addition, the data trends (speed of increasing or decreasing values) are also important indicators that require careful monitoring by the system.

Ethical issues

To assure the user's privacy all the personal data should be protected. Data encryption must be used to transfer data securely both from the client side to the server side and from the server side to the KB. Additionally, data encryption must also be used to safely store the data.

The sensitive data flow is shown in Figure 3. All the sensitive data, such as the user's identity and location, are exclusively stored locally on the client side. Only when an emergency occurs, the client sends the user's identity and location to the server. In this circumstance, a medical alert is triggered so that medical assistance can be provided to the user. It should be noted that in this preliminary study, the user's identity and location are manually encoded on the client software. In the future, a simple graphical user interface may allow to input the user's identity while a positioning system may be integrated to track the user's location [START_REF] Sanfilippo | XBee positioning system with embedded haptic feedback for dangerous offshore operations: a preliminary study[END_REF].

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The non-sensitive data flow is shown in Figure 4. Whenever the client collects new sensor data, the communication link availability is checked. If the communication link is not available, then the new data are temporarily stored locally. Whenever the communication link is available, data are sent from the client to the server. On the server side, the data consistency is checked against the KB. If no similar data are available on the KB, then the data are sent from the server to the KB. This process can help generate the type of robust data that is invaluable to medical researchers.

Simulation results

The main focus of this work is on building the system architecture and validating the communication pattern. Therefore, simulation experiments are performed with simulated data rather than real sensor data. In particular, different sample data from different open access databases are considered. Portions of these data are fed to the client to simulate real sensor measurements.

Concerning ECG monitoring, we use data from the Physiobank archive [START_REF] Moody | Physionet: a web-based resource for the study of physiologic signals[END_REF]. Within this archive, the MIT-BIH Arrhythmia Database [START_REF] Goldberger | Physiobank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals[END_REF] is considered. This database consists of 48 half-hour excerpts of two-channel ambulatory ECG recordings, obtained from 47 subjects. By using this dataset, the possibility of detecting supraventricular premature or ectopic beats (atrial or nodal) [START_REF] Mcnames | Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes[END_REF] is considered. While the sinoatrial node typically regulates the heartbeat during normal sinus rhythm, ectopic

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beats occur when another region of the atria depolarises before the sinoatrial node and thus triggers a premature heartbeat. Hence, a simply way to detect this event has been developed which consists of comparing the current beat time interval with the average time interval of the previous beats. If the current beat time interval is shorter than the average beat time interval, then the system detects a potential ectopic beat. For instance, this occurrence is highlighted in Figure 5, where a ECG segment plot is shown. This arrhythmia is a quite common occurrence in all ages and usually is not serious, therefore the system considers this case as a potentially abnormal condition but not as an extremely dangerous state. When this happens, the corresponding server-side monitoring thread sends a status update to the client so that the vibration motor can vibrate with low frequency and the colour of the LED can be changed to yellow.

With regard to the accelerometer sensor, the possibility of detecting five different user positions is considered. By using the software library provided with the e-Health Sensor Shield, the proposed system is able to distinguish between the following positions: standing/sitting, supine, prone, left and right. A particularly dangerous situation that can happen is fainting, which may cause the user to fall. For instance, this occurrence is highlighted in Figure 6, where the system detects a prone position for the wearer. This situation is quite dangerous and therefore the system considers this case the most critical state. When this happens, the corresponding server-side monitoring thread sends a status update to the client so that the vibration motor can vibrate with high frequency and the colour of the LED can be changed to red. A time plot of a simulated scenario is shown in Figure 7. This time plot shows the occurrences of a supine/prone position and a left/right position respectively. It should be noted that the supine and prone positions are considered equally dangerous for the user as well as the left and right positions.

Regarding the temperature monitoring, the possibility of detecting states of fever and hyperpyrexia for the user is considered. Particularly, axillary body temperature measurements are taken at 10-minutes intervals. For the sake of illustration, the case of hyperthermia is considered as an example. This occurrence is highlighted in Figure 8, where a temperature of 38.12! C is measured. This is quite dangerous for the user, therefore the system considers this case as a critical state and makes the motor to vibrate with high frequency, while the colour of the LED is changed to red. ;<=>678 ?"#$%&")1>()&)$ @$:0"1)>A'$"%9>()1"&)$ B'CD'$%&0$'>5'15)$ aging is widespread across the world. This issue is most advanced in the most highly developed countries, but it is growing faster in less developed regions, which means that older persons will be increasingly concentrated in the less developed regions of the world [START_REF] Lutz | The coming acceleration of global population ageing[END_REF]. In this perspective, there is an urgent need for developing a low-cost solution that will allow to monitor the health state and welfare of the elderly people. Such a system may make it possible for elderly people to live longer in their own homes.

The possibility of developing wearable sensor-based systems for health monitoring of elderly people has been investigated by several research groups. For instance, some usage models for health monitoring systems in daily environments based on wearable and ambient sensors were presented in [START_REF] Korhonen | Health monitoring in the home of the future[END_REF]. An example of a possible implementation of these models was described in [START_REF] Pang | Health monitoring of elderly in independent and assisted living[END_REF] considering the health monitoring of elderly in independent and assisted living. Nonetheless, to the best of our knowledge, a lowcost, versatile and easy to prototype system that integrates a multi-sensor fusion approach with an intuitive haptic feedback for the user has not yet been deeply investigated.

The system described in this paper meets the requirements of low-cost, versatility and rapid-prototyping. It should be noted that the production cost of the chest-worn device can easily be kept below 100 US dollars given the enclosing case, the controller boards, the communication module, the sensor platform, the sensors and the other hardware components. In the future, the production cost could be even further reduced by using a 3-D printing approach or a shape deposition manufacturing (SDM) method to produce the enclosing case. This could make the system affordable for a larger number of elderly people. The system is also versatile since the proposed multilevel architecture allows for adding new software functionalities in a modular way. The possibility of adding new sensors is guaranteed by the modularity of the proposed hardware.

A possible application scenario of the proposed system for this context is described in Figure 9. The elderly is provided with the proposed chest-worn device that allows !"!#$%& '#()*+ '(,-)./"0 897:'&1%" ;'$"1+ <;="0+>?*,1()"3$%"@ Paper-A Wearable Haptic System for the Health Monitoring of Elderly People in Smart Cities for collecting biometric and medical monitoring data of its wearer. The collected data are sent from the client to the server according to the modalities described in Figure 3 and Figure 4. On the server side, the data are checked against the KB. On the KB side, the health measurement data are processed to look for unusual signs or trends. In such a case, an alarm is triggered and a notification is sent to a predefined medical diagnosis center. According to the doctor discretion, an ambulance can be sent to the elder's location so that immediate medical assistance can be provided.

Conclusions and future work

In this paper, a prototype of an integrated wearable health sensor monitoring system was presented. A multi-sensor fusion approach was adopted. The system has the following components embedded in a chest-worn device: a controller board, an accelerometer, a vibration motor, a light-emitting diode (LED) capable of changing colours, a push-button, an ECG sensor and a temperature sensor. This device makes it possible to perform biometric and medical monitoring. It is possible to actuate distinctive haptic feedback patterns in accordance with the wearer's health state thanks to the embedded vibration motor. The embedded colour changing LED provides additional intuitive feedback and the user can report a potential emergency condition by using the push-button. It is possible to use the collected biometric information in real-time for monitoring the health state of the user, or subsequently analyse the data to facilitate a medical diagnosis. The information can be sent wirelessly to a cloud computing system for permanent cloud-based data storage or it can be visualised in real time if sent to a laptop or a smart phone. In this work, the health-monitoring of elderly people was considered as a possible application scenario. Initial simulations were performed to validate the potential of the proposed system. In addition, a conceptual case study was presented to describe the possibility of employing the proposed system in the context of smart cities.

In the future, the use of experimental data will make it possible to certify system performance in a real application scenario. To do this, an extensive field test is necessary involving a large number of users. A comprehensive experimental test would also make it possible to assess the proposed system from a human factor point of view. Another challenge that could be explored in the future is the use of advanced techniques for data mining that draw from the fields of big data, artificial intelligence, machine learning, statistics and database systems by using a knowledge base. Optimisation methods and software libraries similar to the ones proposed in [START_REF] Hatledal | JIOP: a java intelligent optimisation and machine learning framework[END_REF] may be adopted.

In the near future, we expect wearable technology to deliver a key interface and input into the industrial Internet of Things (IoT). The proposed system contributes towards the fulfillment of this idea.

Fig. 1 .

 1 Fig. 1. The concept for a wearable multi-sensor health-monitoring system.

Fig. 2 .

 2 Fig. 2. The proposed system architecture.

  [START_REF]Health Sensor Shield[END_REF] is stacked on top of the adopted communication module. The e-Health Sensor Shield allows Arduino boards to easily gather information from different sensors. An open-source software library is provided with the e-Health Sensor Shield, allowing for easy access to the sensor data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

Fig. 3 .

 3 Fig. 3. Sensitive data flow

Fig. 4 .

 4 Fig. 4. Non-sensitive data flow

Fig. 5 .Fig. 6 .

 56 Fig. 5. An occurrence of supraventricular premature or ectopic beat, which is labeled as "S".

Fig. 7 .

 7 Fig. 7. A time plot of a simulated scenario showing the occurrences of a supine/prone position and a left/right position respectively.

Fig. 8 .

 8 Fig. 8. An occurrence of hyperthermia is detected for the user

Fig. 9 .

 9 Fig. 9. An application scenario for the system concerns the health monitoring of elderly people

http://www.i-joe.org

iJOE -Vol.14, No. 8, 2018

Authors

Filippo Sanfilippo is a member of the Cyber Physical and Applied Smart Systems Research Group, Dept. of Science and Industry systems, Faculty of Technology, Natural Sciences and Maritime Sciences, University College of Southeast Norway (USN), 3603 Kongsberg, Norway. Email: filippo.sanfilippo@usn.no.

Claudio Pacchierotti is a member of the CNRS, University of Rennes, Inria, IRISA, 35000 Rennes, France. Email: claudio.pacchierotti@irisa.fr.