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Grégory Ben-Sadoun,1,2 Emeline Michel,3,4 Cédric Annweiler,1,5– 7 Guillaume Sacco3,5,8 1Department of Geriatric Medicine and Memory Clinic, Research Center on Autonomy and Longevity, University Hospital of Angers, Angers, France; 2Normandie Université, UNICAEN, INSERM, COMETE, CYCERON, CHU Caen, Caen, 14000, France; 3Université Côte d’Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique du Cerveau et du Mouvement, Nice, France; 4Université Côte d’Azur, LAMHESS, Nice, France; 5Laboratoire de Psychologie des Pays de la Loire, Univ Angers, Université de Nantes, EA 4638 LPPL, SFR CONFLUENCES, Angers, F-49000, France; 6School of Medicine, Health Faculty, University of Angers, Angers, France; 7Robarts Research Institute, Department of Medical Biophysics, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, Canada; 8Université Côte d’Azur, CoBTek, Nice, FranceCorrespondence: Grégory Ben-SadounDepartment of Geriatric Medicine and Memory Clinic, Research Center on Autonomy and Longevity, University Hospital of Angers, Angers, FranceEmail bensadoun.gregory@hotmail.fr; gregory.bensadoun@chu-angers.fr; gregory.ben-sadoun@unicaen.frAbstract: Systems using passive infrared sensors with a low resolution were recently proposed to answer the dilemma effectiveness–ethical considerations for human fall detection by Information and Communication Technologies (ICTs) in older adults. How effective is this type of system? We performed a systematic review to identify studies that investigated the metrological qualities of passive infrared sensors with a maximum resolution of 16× 16 pixels to identify falls. The search was conducted on PubMed, ScienceDirect, SpringerLink, IEEE Xplore Digital Library, and MDPI until November 26– 28, 2020. We focused on studies testing only these types of sensor. Thirteen articles were “conference papers”, five were “original articles” and one was a found in arXiv.org (an open access repository of scientific research). Since four authors “duplicated” their study in two different journals, our review finally analyzed 15 studies. The studies were very heterogeneous with regard to experimental procedures and detection methods, which made it difficult to draw formal conclusions. All studies tested their systems in controlled conditions, mostly in empty rooms. Except for two studies, the overall performance reported for the detection of falls exceeded 85– 90% of accuracy, precision, sensitivity or specificity. Systems using two or more sensors and particular detection methods (eg, 3D CNN, CNN with 10-fold cross-validation, LSTM with CNN, LSTM and Voting algorithms) seemed to give the highest levels of performance (> 90%). Future studies should test more this type of system in real-life conditions.Keywords: fall detection, older adults, passive infrared sensor, thermal sensor, thermopile

Grégory Ben-Sadoun,1,2 Emeline Michel,3,4 Cédric Annweiler,1,5–7 Guillaume Sacco3,5,8 1Department of Geriatric Medicine and Memory Clinic, Research Center on Autonomy and Longevity, University Hospital of Angers, Angers, France; 2Normandie Université, UNICAEN, INSERM, COMETE, CYCERON, CHU Caen, Caen, 14000, France; 3Université Côte d’Azur, Centre Hospitalier Universitaire de Nice, Clinique Gériatrique du Cerveau et du Mouvement, Nice, France; 4Université Côte d’Azur, LAMHESS, Nice, France; 5LPPL, Laboratoire de Psychologie des Pays de la Loire, Univ Angers, Université de Nantes, EA 4638 LPPL, SFR CONFLUENCES, Angers, F-49000, France; 6School of Medicine, Health Faculty, University of Angers, Angers, France; 7Robarts Research Institute, Department of Medical Biophysics, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, Canada; 8Université Côte d’Azur, CoBTek, Nice, FranceCorrespondence: Grégory Ben-Sadoun, Department of Geriatric Medicine and Memory Clinic, Research Center on Autonomy and Longevity, University Hospital of Angers, Angers, France, Email gregory.ben-sadoun@unicaen.fr View the original paper by Dr Ben-Sadoun and colleagues This is in response to the Letter to the Editor

G Sacco,1–3,* JM Turpin,3,4,* A Marteu,5 C Sakarovitch,6 B Teboul,2 L Boscher,4,5 P Brocker,4 P Robert,1–3 O Guerin2,3,7 1Memory Center, Claude Pompidou Institut, Department of Geriatrics, University Hospital of Nice, Nice, France; 2Centre d’Innovation et d’Usages en Santé (CIU-S), University Hospital of Nice, Cimiez Hospital, Nice, France; 3CoBTeK Cognition Behaviour Technology EA 7276, Research Center Edmond and Lily Safra, Nice Sophia-Antipolis University, Nice, France; 4Rehabilitation Unit, Department of Geriatrics, University Hospital of Nice, Cimiez Hospital, Nice, France; 5Rehabilitation Unit, Department of Neurosciences, University Hospital of Nice, L’Archet Hospital, Nice, France; 6Department of Clinical Research and Innovation, University Hospital of Nice, Cimiez Hospital, Nice, France; 7Acute Geriatrics Unit, Department of Geriatrics, University Hospital of Nice, Cimiez Hospital, Nice, France *These authors contributed equally to this work Background and purpose: Musculoskeletal system deterioration among the aging is a major reason for loss of autonomy and directly affects the quality of life of the elderly. Articular evaluation is part of physiotherapeutic assessment and helps in establishing a precise diagnosis and deciding appropriate therapy. Reference instruments are valid but not easy to use for some joints. The main goal of our study was to determine reliability and intertester reproducibility of the MP-BV, an inertial sensor (the MotionPod® [MP]) combined with specific software (BioVal [BV]), for elbow passive range-of-motion measurements in geriatrics. Methods: This open, monocentric, randomized study compared inertial sensor to inclinometer in patients hospitalized in an acute, post-acute, and long-term-care gerontology unit. Results: Seventy-seven patients (mean age 83.5±6.4 years, sex ratio 1.08 [male/female]) were analyzed. The MP-BV was reliable for each of the three measurements (flexion, pronation, and supination) for 24.3% (CI 95% 13.9–32.8) of the patients. Separately, the percentages of reliable measures were 59.7% (49.2–70.5) for flexion, 68.8% (58.4–79.5) for pronation, and 62.3% (51.2–73.1) for supination. The intraclass correlation coefficients were 0.15 (0.07–0.73), 0.46 (0.27–0.98), and 0.50 (0.31–40 0.98) for flexion, pronation, and supination, respectively.Conclusion: This study shows the convenience of the MP-BV in terms of ease of use and of export of measured data. However, this instrument seems less reliable and valuable compared to the reference instruments used to measure elbow range of motion in gerontology. Keywords: reliability, intertester reproducibility, inclinometer

Guillaume Sacco,1–3 Véronique Joumier,1,4 Nelly Darmon,1 Arnaud Dechamps,1,5 Alexandre Derreumaux,1,3 Ji-Hyun Lee,2 Julie Piano,2 Nathalie Bordone,2 Alexandra Konig,1,6 Bernard Teboul,3 Renaud David,1,2 Olivier Guerin,1,3 François Bremond,1,4 Philippe Robert1,21EA CoBTeK, Université de Nice Sophia-Antipolis, 2Centre Mémoire de Ressource et de Recherche, CHU de Nice, 3Plateforme Patient du Centre d'Innovation et d'Usage en Santé, CHU de Nice, 4Equipe Stars, Institut National de Recherche en Informatique et en Automatique (INRIA), Sophia-Antipolis, France; 5University of Pancasila, Department of Psychology, Jakarta, Indonesia; 6University of Maastricht, Faculty of Psychology and Neuropsychology, Department of Psychiatry and Neuropsychology, Maastricht, The NetherlandsBackground: One of the key clinical features of Alzheimer's disease (AD) is impairment in daily functioning. Patients with mild cognitive impairment (MCI) also commonly have mild problems performing complex tasks. Information and communication technology (ICT), particularly techniques involving imaging and video processing, is of interest in order to improve assessment. The overall aim of this study is to demonstrate that it is possible using a video monitoring system to obtain a quantifiable assessment of instrumental activities of daily living (IADLs) in AD and in MCI.Methods: The aim of the study is to propose a daily activity scenario (DAS) score that detects functional impairment using ICTs in AD and MCI compared with normal control group (NC). Sixty-four participants over 65 years old were included: 16 AD matched with 10 NC for protocol 1 (P1) and 19 MCI matched with 19 NC for protocol 2 (P2). Each participant was asked to undertake a set of daily tasks in the setting of a “smart home” equipped with two video cameras and everyday objects for use in activities of daily living (8 IADLs for P1 and 11 for P2, plus 4 temporal execution constraints). The DAS score was then computed from quantitative and qualitative parameters collected from video recordings.Results: In P1, the DAS score differentiated AD (DASAD,P1 = 0.47, 95% confidence interval [CI] 0.38–0.56) from NC (DASNC,P1 = 0.71, 95% CI 0.68–0.74). In P2, the DAS score differentiated MCI (DASMCI,P2 = 0.11, 95% CI 0.05–0.16) and NC (DASNC,P2 = 0.36, 95% CI 0.26–0.45).Conclusion: In conclusion, this study outlines the interest of a novel tool coming from the ICT world for the assessment of functional impairment in AD and MCI. The derived DAS scores provide a pragmatic, ecological, objective measurement which may improve the prediction of future dementia, be used as an outcome measurement in clinical trials and lead to earlier therapeutic intervention.Keywords: functional impairment, ICT, IADL, MCI