Multimodal sensor-based fall detection within the domestic environment of elderly people.

BACKGROUND: Falls represent a major threat to the health of the elderly and are a growing burden on the healthcare systems. With the growth of the elderly population within most societies efficient fall detection becomes increasingly important; however, existing fall detection systems still fail to produce reliable results. OBJECTIVES: A study was carried out on sensor-based fall detection, analysis of falls with the help of fall protocols and the analysis of user acceptance of fall detection sensor technology through questionnaires. MATERIAL AND METHODS: A total of 28 senior citizens were recruited from a German community-dwelling population. The primary goal was a sensor-based detection of falls with accelerometers, video cameras and microphones. Details of the falls were analyzed with the help of medical geriatric assessments and standardized fall protocols. The study duration was 8 weeks and required a maximum of nine visits per subject. RESULTS: The study participants were 28 subjects with a mean age of 74.3 and a standard deviation (SD) of ± 6.3 years of which 12 were male and 16 female. A total of 1225.7 measurement days were recorded from all participants and the algorithms detected 2.66 falls per day. During the study period 15 falls occurred and 12 of these falls were correctly recognized by the fall detection system. CONCLUSION: Current fall detection technologies work well under laboratory conditions but it is still problematic to produce reliable results when these technologies are applied to real life conditions. Acceptance towards the sensors decreased after study participation although the system was generally perceived as useful or very useful.

GAL@Home: a feasibility study of sensor-based in-home fall detection.

BACKGROUND: A considerable proportion of falls occur within the domestic environment. Sensor-based identification of falls in seniors' homes could help them to remain autonomous and self-sufficient in their own homes. The objective of this study was to evaluate fall detection systems within the home environment using optical and accelerometric sensor systems. METHODS: Portable triaxial accelerometers and optical sensors were used to detect falls in subjects with known problems of mobility and a recent fall history. RESULTS: Three subjects were investigated with the system. Overall nine falls occurred during the study period. Four falls were recorded by the accelerometric system and one fall by the optical system. Subjects with increased risk of falling as measured with mobility and fall risk assessments tend to fall more frequently. CONCLUSION: The study shows that there is a considerably large difference between fall-detector evaluation studies in domestic environments and in laboratory trials.

Defining the user requirements for wearable and optical fall prediction and fall detection devices for home use.

One of the major problems in the development of information and communication technologies for older adults is user acceptance. Here we describe the results of focus group discussions that were conducted with older adults and their relatives to guide the development of assistive devices for fall detection and fall prevention. The aim was to determine the ergonomic and functional requirements of such devices and to include these requirements in a user-centered development process. A semi-structured interview format based on an interview guide was used to conduct three focus group discussions with 22 participants. The average age was 75 years in the first group, 68 years in the second group and 50 years in the third group (relatives). Overall, participants considered a fall prediction system to be as important as a fall detection system. Although the ambient, unobtrusive character of the optical sensor system was appreciated, wearable inertial sensors were preferred because of their wide range of use, which provides higher levels of security. Security and mobility were two major reasons for people at risk of falling to buy a wearable and/or optical fall prediction and fall detection device. Design specifications should include a wearable, non-stigmatising sensor at the user's wrist, with an emergency option in case of falling.

Parallel processing of social signals by the mammalian main and accessory olfactory systems.

The mammalian olfactory system has evolved complex mechanisms to detect a vast range of molecular cues. In rodents, the olfactory system comprises several distinct subsystems. Current interest has focused on the exact role that each of these subsystems plays in detecting molecular information and regulating chemosensory-dependent behaviors. Here, we summarize recent results showing that the mouse main and accessory olfactory systems detect, at least in part, overlapping sets of social chemosignals. These findings give rise to a model that involves parallel processing of the same molecular cues in both systems. Together with previous work, this model will lead to a better understanding of the general organization of chemical communication in mammals and give a new direction for future experiments.