On the Development of a Resident Monitoring System:Usability, Privacy and Security Aspects

Worldwide, the elderly have suffered disproportionately from the effects of the COVID-19 pandemic, both in terms of their prognosis once contracted the disease and in terms of the preventative measures required for this demographic, who are at much higher risk than the rest of the population. In the “new normal”, the well-being of older adults (residing either in their own homes or in care homes) will be ideally monitored remotely. These measures would preserve the independence of individuals without compromising on their safety. In this paper we discuss aspects of the design and implementation of a resident monitoring system (RMS) with particular emphasis on overcoming the barriers for adoption among these populations, by addressing the aspects of usability, privacy and security at the core of the development of such a system. We discuss the current challenges of this research and future work on the RMS

A Machine Learning Multi-Class Approach for Fall Detection Systems Based on Wearable Sensors with a Study on Sampling Rates Selection

Falls are dangerous for the elderly, often causing serious injuries especially when the fallen person stays on the ground for a long time without assistance. This paper extends our previous work on the development of a Fall Detection System (FDS) using an inertial measurement unit worn at the waist. Data come from SisFall, a publicly available dataset containing records of Activities of Daily Living and falls. We first applied a preprocessing and a feature extraction stage before using five Machine Learning algorithms, allowing us to compare them. Ensemble learning algorithms such as Random Forest and Gradient Boosting have the best performance, with a Sensitivity and Specificity both close to 99%. Our contribution is: a multi-class classification approach for fall detection combined with a study of the effect of the sensors’ sampling rate on the performance of the FDS. Our multi-class classification approach splits the fall into three phases: pre-fall, impact, post-fall. The extension to a multi-class problem is not trivial and we present a well-performing solution. We experimented sampling rates between 1 and 200 Hz. The results show that, while high sampling rates tend to improve performance, a sampling rate of 50 Hz is generally sufficient for an accurate detection

Dedicated photoreceptor pathways in Drosophila larvae mediate navigation by processing either spatial or temporal cues.

To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways

uMove: a wholistic framework to design and implement ubiquitous computing systems supporting user's activity and situation

Cette thèse présente un ensemble d'outils (un framework) qui permettent la définition, la création et la réalisation de systèmes informatiques ubiquitaires pouvant intégrer la prise en charge des activités des utilisateurs ainsi que de la détection de leur situation. Avec le rapide développement de l'informatique intégrant les contextes des utilisateurs ainsi que l'informatique mobile, de nouveaux défis sont apparus et parmi ceux-ci, trois d'entre eux sont adresses dans cette thèse. Le premier est le besoin d'un ensemble d'outils permettant le développement de systèmes ubiquitaires partant de leur définition théorique jusqu'à leur réalisation. Le deuxième défi consiste à développer des applications intelligentes qui intégrantes les nouvelles technologies telles que les senseurs et l'accès à des systèmes informatiques repartis. Le troisième défi est l'intégration d'interactions homme-machine enrichies par la prise en compte des mouvements, des activités et situations des utilisateurs ceci par le biais de senseurs de plus en plus présents dans nos environnements et sur les dispositifs informatiques mobiles. Dans cette thèse, nous décrivons uMove, un ensemble d'outils permettant la définition et le développement de système ubiquitaire représentant différentes sortes d'environnements physiques ou logiques. uMove comporte trois facettes qui décrivent les concepts fondamentaux ainsi que les outils logiciels nécessaires à leur développement. La première facette est consacrée à la définition du modèle conceptuel décrivant des systèmes ubiquitaires composés d'entités et d'observateurs et ceci en utilisant une approche systémique. La deuxième facette présente une architecture qui permet aux concepteurs et développeurs de formaliser leurs systèmes. La troisième facette décrit les outils logiciels qui permettront d'implémenter les projets définis de manière systémique et en respectant l'architecture uMove. Finalement, uMove est évalué et son modèle validé à travers quatre projets qui ont été implémentés avec l'ensemble de ces outils.This thesis presents a framework that offers tools for the design and the implementation of Ubiquitous computing systems supporting user motions, activities and situations. With the rapid development of context-aware mobile computing and sensor-based interaction, many new challenges come up, three of which are particularly addressed in this thesis. The first is the need for wholistic tools to develop Ubiquitous computing infrastructures. The second concerns smart applications allowing users to benefit from the distributed computing power in their environment, and the third is the integration of enriched human-computer interaction using motions, activity and situation provided by the increasing sensing capabilities of the user environment or mobile devices. We propose the uMove framework, a comprehensive solution which allows to design and develop Ubicomp systems representing different kinds of physical or virtual environments based on a systemic approach. uMove proposes both theoretical foundations and implementation tools and is divided into three specific facets. The first facet is the conceptual model describing a Ubiquitous computing system made of entities and observers within their physical or logical environment. The second facet is a system architecture which offers designers and developers the tools to theoretically define a logical system, including the types of contexts taken into consideration. The third facet is development tools that allow programmers to implement their systems, sensors, applications and services. The uMove framework is evaluated and validated in an interactive manner through four projects

A comparison of machine learning algorithms for fall detection using wearable sensors

The proportion of people 60 years old and above is expected to double globally to reach 22% by 2050. This creates societal challenges such as the increase of age-related illnesses and the need for caregivers. Falls are a major threat for the elderly, often causing serious injuries especially when the fallen person stays on the ground for a long time without assistance.This paper presents the development of a Fall Detection System (FDS) using an accelerometer combined with a gyroscope worn at the waist. Data come from SisFall, a publicly available dataset containing records of Activities of Daily Living and falls. We compared five Machine Learning algorithms. We first applied preprocessing and a feature extraction stage before using five Machine Learning algorithms, allowing us to compare them. Ensemble learning algorithms such as Random Forest andGradient Boosting have the best performance, with a Sensitivity and Specificity both close to 99%

NONO couples the circadian clock to the cell cycle

Mammalian circadian clocks restrict cell proliferation to defined time windows, but the mechanism and consequences of this interrelationship are not fully understood. Previously we identified the multifunctional nuclear protein NONO as a partner of circadian PERIOD (PER) proteins. Here we show that it also conveys circadian gating to the cell cycle, a connection surprisingly important for wound healing in mice. Specifically, although fibroblasts from NONO-deficient mice showed approximately normal circadian cycles, they displayed elevated cell doubling and lower cellular senescence. At a molecular level, NONO bound to the p16-Ink4A cell cycle checkpoint gene and potentiated its circadian activation in a PER protein-dependent fashion. Loss of either NONO or PER abolished this activation and circadian expression of p16-Ink4A and eliminated circadian cell cycle gating. In vivo, lack of NONO resulted in defective wound repair. Because wound healing defects were also seen in multiple circadian clock-deficient mouse lines, our results therefore suggest that coupling of the cell cycle to the circadian clock via NONO may be useful to segregate in temporal fashion cell proliferation from tissue organization

Feature Article: NONO couples the circadian clock to the cell cycle

Mammalian circadian clocks restrict cell proliferation to defined time windows, but the mechanism and consequences of this interrelationship are not fully understood. Previously we identified the multifunctional nuclear protein NONO as a partner of circadian PERIOD (PER) proteins. Here we show that it also conveys circadian gating to the cell cycle, a connection surprisingly important for wound healing in mice. Specifically, although fibroblasts from NONO-deficient mice showed approximately normal circadian cycles, they displayed elevated cell doubling and lower cellular senescence. At a molecular level, NONO bound to the p16-Ink4A cell cycle checkpoint gene and potentiated its circadian activation in a PER protein-dependent fashion. Loss of either NONO or PER abolished this activation and circadian expression of p16-Ink4A and eliminated circadian cell cycle gating. In vivo, lack of NONO resulted in defective wound repair. Because wound healing defects were also seen in multiple circadian clock-deficient mouse lines, our results therefore suggest that coupling of the cell cycle to the circadian clock via NONO may be useful to segregate in temporal fashion cell proliferation from tissue organization