Risk factors for falls and technologies for fall risk assessment in older adults: Dissertation

Falls are a serious cause of morbidity and costs to society and frequent falls are associated with impaired quality of life of older people. Screening for high fall risk persons among the older population consumes resources and public funding. Novel, low-cost methods for identifying older persons at high fall risk are thus needed to be able to target preventive actions. The aim of this study was to examine whether individual clustering of chronic diseases is associated with higher fall risk and how technical solutions and connected data, with a special focus on the use of accelerometers, can be utilized in measuring acutely or incrementally appearing risk factors for falls in older adults. The research was carried out by collecting population-based survey data on older people (age 65–98) and by utilizing existing databases. A total of 918 people filled in a questionnaire including items on health status, lifestyle and falls. In addition, 42 volunteers participated in large-scale fall risk measurements. During the measurements, accelerometers were attached to the lumbar spine and front hip of the subject. A mobile application utilizing a separate accelerometer was developed to assess the risk of falls. The feasibility of the mobile application was tested with 11 volunteers of working age. In addition, an easy-to-use application for home-based training was developed and user experiences were collected from six older test subjects in Finland and ten older subjects in Spain. In Spain, four healthcare professionals evaluated the applicability and usability of the application. The results of the study showed that chronic diseases and multiple morbidity are associated with an increased risk of falling. Several technologies have been developed to assess the risk of a fall. Preliminary results indicated that a mobile application utilizing a separate accelerometer can detect deficiencies in walking style, which, in turn, may indicate an increased risk of falling. This study also showed that a sensor attached to the front of the hip could reliably assess some of the gait features associated with fall risk. Both the older people themselves and health care professionals felt positive about the home-based exercise application.