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Aims: The fall rate in urgency urinary incontinence (UUI) and mixed UI (MUI) older women is higher when compared with that of continent women. One hypothesis is that a strong desire to void (SDV) could alter gait parameters and therefore increase the risk of falls. The aim of this study was to investigate and compare the effect of SDV on gait parameters in UUI/MUI and continent older women who experienced falls. The secondary aim was to determine the relationship between UI severity and gait parameters in incontinent women., Methods: A quasi-experimental pilot study was conducted with two groups of healthy community-dwelling women who experienced at least one fall in the last year: continent (n = 17; age: 74.1 ± 4.3) and UUI/MUI (n = 15; age: 73.5 ± 5.9). We recorded, analyzed, and compared spatiotemporal gait parameters for participants in each group with both SDV and no desire to void condition., Results: A pattern of reduced velocity (P = 0.05) and stride width (P = 0.02) was observed in both groups with SDV. Incontinence severity was correlated with reduced velocity (r s  = -0.63, P = 0.01), increased stance time (r s = 0.65, P = .01) and stance time variability (r s  = 0.65, P = .01) in no desire to void condition and with reduced velocity (r s  = -0.56, P = .03) and increased stride length variability (r s  = 0.54, P = .04) in SDV condition., Conclusions: SDV reduced gait velocity and stride width regardless of continence status in older women at risk of falls. Further, UI severity in the UUI/MUI women was correlated to reduced gait velocity and increased variability. Our findings could explain the higher fall rate in this population., (© 2019 Wiley Periodicals, Inc.)

Description: Gerontechnologies can be used to detect accidental falls. However, existing systems do not entirely meet users' expectations. Our team developed an intelligent video-monitoring systems to fill these gaps. Authors advocate consulting potential users at the early stages of the design of gerontechnologies and integrating their suggestions., Purpose: This study aims to explore health care workers' opinion regarding the intelligent video monitoring to detect falls by older adults living at home., Method: This qualitative study explored the opinions of 31 participants using focus groups. Transcripts were analyzed using predetermined codes based on the competence model., Findings: Participants reported several advantages for using the intelligent video monitoring and provided suggestions for improving its use., Implications: The participants' suggestions and comments will help to improve the system and match it to users' needs., (© CAOT 2015.)

Purpose: To examine whether patients with age-related macular degeneration (AMD), glaucoma, or Fuchs corneal dystrophy report limiting their activity due to a fear of falling as compared with a control group of older adults with good vision., Methods: We recruited 345 patients (93 with AMD, 57 with Fuchs, 98 with glaucoma, and 97 controls) from the ophthalmology clinics of Maisonneuve-Rosemont Hospital (Montreal, Canada) to participate in a cross-sectional study from September 2009 until July 2012. Control patients who had normal visual acuity and visual field were recruited from the same clinics. Participants were asked if they limited their activity due to a fear of falling. Visual acuity, contrast sensitivity, and visual field were measured and the medical record was reviewed., Results: Between 40% and 50% of patients with eye disease reported activity limitation due to a fear of falling compared with only 16% of controls with normal vision. After adjustment for age, sex, race, number of comorbidities, cognition, and lens opacity, the Fuchs groups was most likely to report activity limitation due to a fear of falling (odds ratio [OR] = 3.07; 95% confidence interval [CI], 1.33-7.06) followed by the glaucoma group (OR = 2.84; 95% CI, 1.36-5.96) and the AMD group (OR = 2.42; 95% CI, 1.09-5.35). Contrast sensitivity best explained these associations., Conclusions: Activity limitation due to a fear of falling is very common in older adults with visually impairing eye disease. Although this compensatory strategy may protect against falls, it may also put people at risk for social isolation and disability.

According to the demographic evolution in industrialized countries, more and more elderly people will experience falls at home and will require emergency services. The main problem comes from fall-prone elderly living alone at home. To resolve this lack of safety, we propose a new method to detect falls at home, based on a multiple-cameras network for reconstructing the 3-D shape of people. Fall events are detected by analyzing the volume distribution along the vertical axis, and an alarm is triggered when the major part of this distribution is abnormally near the floor during a predefined period of time, which implies that a person has fallen on the floor. This method was validated with videos of a healthy subject who performed 24 realistic scenarios showing 22 fall events and 24 cofounding events (11 crouching position, 9 sitting position, and 4 lying on a sofa position) under several camera configurations, and achieved 99.7% sensitivity and specificity or better with four cameras or more. A real-time implementation using a graphic processing unit (GPU) reached 10 frames per second (fps) with 8 cameras, and 16 fps with 3 cameras.

The GEM scale is an objective assessment tool evaluating walking safety of elderly individuals. It includes 33 walking items divided into three subscales (A, B, and C). The purpose of this study was to estimate the internal consistency and factorial validation of the scale. Seventy-four subjects (> or = 65 years) recruited from geriatric units were assessed by a total of 11 physical therapists. The internal consistency data were analyzed by using the Cronbach alpha coefficient. An exploratory factor analysis was performed to analyze the factorial structure of the scale and determine the construct validation. The internal consistency for the three subscales revealed high Cronbach alpha (subscales A = 0.90; B = 0.76, and C = 0.85). The preliminary analyses of the factorial validation did not confirm the original structure of the scale. For subscales A and B, a three-factor solution was supported by the analyses and explained 61% of the total variance. For subscale C, a four-factor solution was extracted and explained 87% of the total variance. The three subscales showed excellent item homogeneity. The factorial validation results support a new structure for the GEM scale regrouping the items in two sub-scales under different factors. The reorganization of the walking items into representative factors will allow a better understanding and interpretation of the scale.

We explored the perception and receptivity of elderly people regarding the introduction of an intelligent videomonitoring system (IVS) at home. Using a mixed methods design, 25 elderly people with a history of falls completed a structured interview (two questionnaires). In the year preceding the interview, 72% of the participants fell as many as seven times. Open-ended questions (qualitative data) were used to supplement the quantitative data. A content analysis (qualitative data) and a descriptive analysis (quantitative data) were carried out. The participants were 84% favourable or partially favourable to technologies which ensured home security and 96% favourable or partially favourable to the IVS. About half (48%) said that they would use it. The other participants did not wish to use it unless they had been left to live alone or if their health condition worsened. Thus the living conditions of the elderly appear to influence their perception and receptivity regarding the acceptance and use of an IVS.

Today, different ways are suggested to help elderly people in case of emergency. Our aim here is to propose a novel method, without any wearable device, to detect falls on the floor with a multiple cameras system. This proposal uses image analysis to localise people and reconstruct their 3D shape and position. The particularity of this contribution is the use of cameras sharing a large common field of view. Experimental results obtained with 14 different fall scenarios and 14 normal daily activities showed a 100% fall detection efficiency.

Faced with the growing population of seniors, Western societies need to think about new technologies to ensure the safety of elderly people at home. Computer vision provides a good solution for healthcare systems because it allows a specific analysis of people behavior. Moreover, a system based on video surveillance is particularly well adapted to detect falls. We present a new method to detect falls using a single camera. Our approach is based on the 3D trajectory of the head, which allows us to distinguish falls from normal activities using 3D velocities.

Description. Les gérontechnologies peuvent être utilisées pour la détection des chutes. Toutefois, les systèmes existants ne répondent pas entièrement aux besoins des usagers. Notre équipe a donc développé un système de vidéosurveillance intelligente pour combler certaines lacunes. Des auteurs préconisent de consulter les utilisateurs potentiels des gérontechnologies dès les premiers stades de la conception pour y intégrer leurs suggestions. But. L’étude vise à explorer l’opinion des acteurs du système de santé concernant la vidéosurveillance intelligente pour la détection des chutes des aînés à domicile. Méthodologie. Une étude qualitative a exploré l’opinion de 31 participants en utilisant la technique de groupe de discussion thématique. Les transcriptions ont été codées à partir de codes prédéfinis, créés à partir du Modèle de compétence. Résultats. Les participants dégagent divers intérêts à la vidéosurveillance intelligente et suggèrent des améliorations au système. Conséquences. Les propositions et réflexions des participants permettront d’améliorer le système pour répondre aux besoins des usagers. [ABSTRACT FROM AUTHOR]

Aim: To explore the conditions that may influence the implementation of an interactive mobile application (app) and an intelligent videomonitoring system (IVS) in nursing homes (NHs) and the ethical challenges of their use. Background: There is a lack of knowledge about implementing technologies in NHs and the ethical challenges that might arise. In past studies, nursing care teams expressed the need for technologies offering clinical support. Technologies like an IVS and an app could prove useful in NHs to prevent and manage falls and responsive behaviours. Design: An exploratory qualitative study was conducted with care managers, family caregivers and formal caregivers in five NHs. Methods: Each participant was shown a presentation of a potential app and a short video on an IVS. It was followed by an individual semi‐structured interview. A conventional content analysis was performed. Findings: Potential users found it would be possible to implement these technologies in NHs even if resistance could be expected. To facilitate adoption and achieve clinical benefits, the implementation of technologies should be pilot‐tested, and coaching activities should be planned. Ethical risks were considered already present in NHs even without technologies, for example, risks to privacy. Strategies were proposed, for instance, to adapt the code of ethics and procedures. Some potential prejudices about the interest and abilities of older staff, nurses' aides, and family caregivers to use technology were identified. Conclusions: Through rigorous and ethical implementation, technologies supporting clinical care processes could benefit older people living in NHs, as well as their relatives and the staff. Implications for practice: Various strategies are proposed to successfully implement technologies. Effort should be made to avoid prejudices during implementation, and procedures should be adapted to mitigate possible ethical challenges. [ABSTRACT FROM AUTHOR]