Sensor technologies and fall prevention

Fall prevention is important for old adults residing at home or in a nursing home. Fall prevention for community-dwelling older adults requires a different approach than for nursing home residents. However, in both cases sensor technologies may contribute to effective and personalized prevention due to their ability to detect small, but essential changes before the manifestation of mobility problems or a fall.

Sensor technologies could be used in nursing homes to monitor residents with dementia 24/7 and give a notification when a high risk fall situation occurs. To develop a fall prevention system it is necessary to determine the type of sensors that are most suitable to monitor residents with dementia, the factors that contribute to a fall, and the requirements end users (nursing staff) think are important for such a system. This thesis addresses these factors and provides a basis for a sensor system that can recognize situations prior to a fall, offering the possibility to intervene early.

Mobility problems are often the underlying cause of a fall. Sensor technology, as a user-friendly and inexpensive device, could detect those mobility problems early in community-dwelling older adults. The thesis shows that smart devices, more specifically the iPod Touch, is a valid and reliable instruments to assess walking and balance abilities. Normative data about changes in gait due to natural aging might be used to detect changes, due to reduced physical functioning or diseases, in an early stage. Consequently, interventions can be started early to prevent further deterioration and reduce the risk of falling.

Dissertation: http://hdl.handle.net/11370/277128fd-ba70-40d6-b45b-cc9f26a98363