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

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

Auditorium of Kastelli research centre. Aapistie 1, Oulu

Topic of the dissertation

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

Doctoral candidate

Master of Science Immonen Milla

Faculty and unit

University of Oulu Graduate School, Faculty of Medicine, Center for Life Course Health Research and Research Unit of Medical Imaging, Physics and Technology

Subject of study

Medical physics and technology

Opponent

Professor Sari Stenholm, University of Turku

Custos

Professor Raija Korpelainen, University of Oulu

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Fall risk of older adults can be predicted by techological solutions

Doctoral dissertation shows that the fall risk of older people can be assessed automatically by utilizing technologies. The study found that a mobile application with a separate accelerometer attached to the lumbar spine was able to reliably detect features from walking style that predict falling.

In addition, a sensor attached to the front of the hip was able to reliably detect some of the features predicting high fall risk. Feedback of tested home training technology was mainly positive from older and professional test users.

In particular, the dissertation examined the accelerometer-based methods and the suitability of the mobile application developed by VTT for risk assessment. In addition, the study tested the suitability of the technology for home training to reduce the fall risk. Injurious falls cause high healthcare costs and can lead to long-term institutional care for the elderly. As the population ages, it is important to find effective ways to prevent falls. Personalized screening and prevention of the risk of falls is expensive and time consuming and it is important to find new and reliable methods for screening people at high fall risk. Mobile and sensor technologies provide new possibilities for screening individuals at high risk of falling.
Last updated: 31.1.2020