Céline Franco

iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System

This paper proposes an implementation of a Kalman filter, using inertial sensors of a smartphone, to estimate 3-D angulation of the trunk. The developed system monitors the trunk angular evolution during bipedal stance and helps the user to improve balance through a configurable and integrated auditory-biofeedback (ABF) loop. A proof-of-concept study was performed to assess the effectiveness of this so-called iBalance-ABF-smartphone-based audio-biofeedback system-in improving balance during bipedal standing. Results showed that young healthy individuals were able to efficiently use ABF on sagittal trunk tilt to improve their balance in the medial-lateral direction. These findings suggest that the iBalance-ABF system as a telerehabilitation system could represent a suitable solution for ambient assisted living technologies.

Wegoto: A Smartphone-based approach to assess and improve accessibility for wheelchair users

This paper proposes a description of a Smartphone-based approach to assess and improve accessibility for wheelchair users. The developed system employs a dedicated Smartphone application that records various complementary sensor measurements (acceleration, deceleration, inclination, orientation, speed, GPS position) and permits obstacle denunciation. Then, accessibility information are reported on maps in a Geographic Information System which can calculate the most accessible route for wheelchair users taking into account their profiles and capabilities. A case study involving a wheelchair-dependent paraplegic was performed to preliminary assess the feasibility of our Smartphone-based approach to provide an accessibility index for wheelchair users. Although preliminary, our results do suggest that the Wegoto system could be used as an innovative assistive navigation system for wheelchair users and ultimately could help to improve their autonomy and quality of life.

Mobile Phone-Based Joint Angle Measurement for Functional Assessment and Rehabilitation of Proprioception

Assessment of joint functional and proprioceptive abilities is essential for balance, posture, and motor control rehabilitation. Joint functional ability refers to the capacity of movement of the joint. It may be evaluated thereby measuring the joint range of motion (ROM). Proprioception can be defined as the perception of the position and of the movement of various body parts in space. Its role is essential in sensorimotor control for movement acuity, joint stability, coordination, and balance. Its clinical evaluation is commonly based on the assessment of the joint position sense (JPS). Both ROM and JPS measurements require estimating angles through goniometer, scoliometer, laser-pointer, and bubble or digital inclinometer. With the arrival of Smartphones, these costly clinical tools tend to be replaced. Beyond evaluation, maintaining and/or improving joint functional and proprioceptive abilities by training with physical therapy is important for long-term management. This review aims to report Smartphone applications used for measuring and improving functional and proprioceptive abilities. It identifies that Smartphone applications are reliable for clinical measurements and are mainly used to assess ROM and JPS. However, there is lack of studies on Smartphone applications which can be used in an autonomous way to provide physical therapy exercises at home.

Evaluation of a Smartphone-based audio-biofeedback system for improving balance in older adults - A pilot study

This study was designed to assess the effectiveness of a Smartphone-based audio-biofeedback (ABF) system for improving balance in older adults. This so-called “iBalance-ABF” system that we recently developed is “all-inclusive” in the sense that its three main components of a balance prosthesis, (i) the sensory input unit, (ii) the processing unit, and (iii) the sensory output unit, are entirely embedded into the Smartphone. The underlying principle of this system is to supply the user with supplementary information about the medial-lateral (ML) trunk tilt relative to a predetermined adjustable “dead zone” through sound generation in earphones. Six healthy older adults voluntarily participated in this pilot study. Eyes closed, they were asked to stand upright and to sway as little as possible in two (parallel and tandem) stance conditions executed without and with the use of the iBalance-ABF system. Results showed that, without any visual information, the use of the Smartphone-based ABF allowed the older healthy adults to significantly decrease their ML trunk sway in the tandem stance posture and to mitigate the destabilizing effect induced by this particular stance. Although an extended study including a larger number of participants is needed to confirm these data, the present results are encouraging. They do suggest that Smartphone-based ABF system could be used for balance training and rehabilitation therapy in older adults.

Estimation of Task Persistence Parameters from Pervasive Medical Systems with Censored Data

This paper compares two statistical models of location within a smart flat during the day. The location is then identified with a task executed normally or repeated pathologically, e.g., in case of Alzheimer disease (AD), whereas a task persistence parameter assesses tendency to perseverate. Compared with a Pólyas urns derived approach, the Markovian one is more effective and offers up to 98 percent of good prediction using only the last known location but distinguishing days of week. To extend these results to a multisensor context, some difficulties must be overcome. An external knowledge is made from a set of observable random variables provided by body sensors and organized either in a Bayesian network or in a reference knowledge base system (KBS) containing the persons actimetric profile. When data missed or errors occurred, an estimate of the joint probabilities of these random variables and hence the probability of all events appearing in the network or the KBS was developed and corrects the bias of the Lancaster and Zentgraf classical approach which in certain circumstances provides negative estimates. Finally, we introduce a correction corresponding to a possible loss of the persons synchronization with the nycthemeral (day versus night) zeitgebers (synchronizers) to avoid false alarms.

Perspectives in Home TeleHealthCare System: Daily Routine Nycthemeral Rhythm Monitoring from Location Data

Free of most social constraints, elderly people tend to perform activities of daily living following the same sequence. This paper proposes a method for medical telesurveillance to detect and quantify a nycthemeral shift in this daily routine. While this common phenomenon is mostly mild, in acute cases, however, it may reveal a pathological behavior requiring a rapid medical examination. This method allows to compare two sequences of activities using the Hamming distance and to interpret the result according to the Gumbel distribution. It may be used to compare either consecutive sequences thereby taking into account evolution in the habits or a sequence to the person’s individual activity profile to detect dementia’s onset. In this early stage, only elementary activities were considered. That is the reason why location data were used to monitor the person’s nycthemeral rhythm of activity. IR sensors placed in her own flat allowed us to follow-up the inhabitant’s successive activities. Improvements of this method have already been planned. They include the use of a multi-sensors network to monitor both actimetric (location, movement, posture) and physiological nycthemeral rhythms (ECG, respiratory frequency) and to detect the use of particular items (fridge, chairs, bed). This more sophisticated sensors network will allow us to monitor more complex tasks execution and then to detect pathological behaviors such as perseveration in a task or wandering. On the other hand, multiplying sensors will require more storage capacities and the use of time-consuming data fusion tools. Therefore, a classification phase will be necessary to reduce as possible the number of relevant sensors.

Smartphone-Based System for Sensorimotor Control Assessment, Monitoring, Improving and Training at Home

This article proposes an innovative Smartphone-based architecture designed to assess, monitor, improve and train sensorimotor abilities at home. This system comprises inertial sensors to measure orientations, calculation units to analyze sensorimotor control abilities, visual, auditory and somatosensory systems to provide biofeedback to the user, screen display and headphones to provide test and/or training exercises instructions, and wireless connection to transmit data. We present two mobile applications, namely “iBalance” and “iProprio”, to illustrate concrete realization of such architecture in the case of at-home autonomous assessment and rehabilitation programs for balance and proprioceptive abilities. Our findings suggest that the present architecture system, which does not involve dedicated and specialized equipment, but which is entirely embedded on a Smartphone, could be a suitable solution for Ambient Assisted Living technologies.