Sensor Technology for Fall Prevention
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (20 October 2021) | Viewed by 21012
Special Issue Editors
Interests: health technology; biomedical engineering; signal processing; wearable body sensors; e-health and m-health; biomedical sensor systems; non-invasive sensor systems; motion analysis; fall detection; fall prevention; blood flow measurements; end-user compliance; user acceptance
Special Issues, Collections and Topics in MDPI journals
Interests: health technology; biomedical engineering; wearable body sensors; e-health and m-health; smart homes; biomedical sensor systems; non-invasive sensor systems; motion analysis; fall detection; fall prevention; health trend monitoring; ensuring safe and secure independent living; end-user compliance; user acceptance; quality of interaction; human–robot interaction; human–computer interaction; human–machine interaction
Special Issues, Collections and Topics in MDPI journals
2. Department of Physiotherapy, School of Health, Care and Social Welfare, Mälardalen University, 721 23 Vasteras, Sweden
3. Research and Development in Sörmland, Region Sörmland, 632 17 Eskilstuna, Sweden
Interests: behavioural medicine; behaviour change techniques; fall prevention exercise and falling techniques for middle- and older-age adults; clinical trials; medical technology and m-health.active and healthy aging; physical activity and exercise; welfare technology
Special Issue Information
Dear Colleagues,
Falls and injuries related to falls are common health problems among older people. There are also almost 40 million non-fatal falls that result in the need for medical attention each year. The financial costs of falls in an acute phase are substantial without accounting for the time needed to recover after a fall injury. Hence, preventing falls is important, not only from an economic perspective but also from the perspective of individual fallers. Falls are commonly associated with decreased participation in social and physical activities and quality of life. Therefore, preventing falls is much more complex than detecting falls. In order to prevent falls, developing means for predicting the occurrence of falls is of the utmost importance. Wearable sensors allow for the monitoring of postures, physical activity levels, and vital signs and the detection of falls.
This Special Issue seeks to explore opportunities and challenges regarding the use of sensors or other technologies for predicting and/or preventing falls. Prospective authors are cordially invited to submit their original contributions related to various aspects of the use of sensor technology for fall prevention. We especially welcome clinical trials, studies that adopt a participatory research design, and systematic reviews. Topics of interest include, but are not limited to:
* technological methods for risk/fall prediction;
* wireless sensors and networks;
* wearable sensors;
* sensor-based feedback on balance/sway to patients and/or care providers;
* sensor-based detection of near-falls;
* reliability and validity of risk/fall predictions;
* patients’ and care providers’ perspectives on sensor technology;
* cost-effectiveness of technologies for preventing falls; and
* the social impact of technologies for preventing falls.
Prof. Dr. Maria Linden
Dr. Annica Kristoffersson
Dr. Marina Arkkukangas
Guest Editors
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