Detection of Floor Level Obstacles and Their Influence on Gait - A Further Step to an Automated Housing Enabling Assessment

Nils Volkening, Andreas Hein
International Journal on Advances in Intelligent Systems
The demographic change in the industrialcountries is a great social challenge. To ensure constant or better (health) care in the next decades, new care concepts for older people are needed. An approach is the use of Information and Communication Technology based solutions. Especially the preservation of personal mobility should be in focus because it is a key role to sustain autonomy and social interaction of senior citizens. In addition to the age-based declining mobility, there are secondary events, which reduce the mobility of senior citizens, e.g. diseases or fall events. Prevention of fall events is a goal for the Housing Enabling Assessments by adaption of room, e.g., by detecting and removing tripping hazards. Former work proves that an automated Housing Enabling Assessment executed by an autonomous service robot could achieve better quality and higher acceptance than a manually controlled Housing Enabling Assessment. In this article, two different methods for detecting relevant unevenness of floor in home environments and resulting challenges are presented. An adapted autonomous service robot is used as well as a Microsoft® Kinect for gait analysis and, regarding the detection of the floor’s unevenness, a Prime Sense ® Carmine 1.08 depth sensor and a self- designed triangulation laser scanner were compared. First results indicate that floor characteristics have a relevant influence on gait parameters, such as gait speed, step / stride length and their variation. Also, results show that floor characteristics should become a mandatory factor for in-home gait analysis.
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Entwicklung neuer Methoden zur Bewegungserfassung von Menschen in Lebens- und Arbeitsumgebungen

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