On Visualization of Movements for Monitoring Older Adults

It is a well-known statistics that the percentage of population of older adults will globally surpass the other age categories. It is also observed that a majority of older adults would prefer to stay at their own place of residence for as long as they can. In support of such an independent living life style, various ambient sensor technologies have been designed which can be deployed for long-term monitoring of movements and activities. Depending on the required level of detail associated with such a monitoring system, spatiotemporal data can be collected during various intervals of daily activities for detecting any on-sets of anomalies. The greater granularity, the deeper the level of detail associated with the movement patterns for instances of time and collective durations. This paper we first presents an overview of various visualization techniques which can be employed for monitoring movement patterns. The paper further presents our results of movement visualization experiments using two sample datasets which can be used as a basis for determining movement anomalies. The first dataset is associated with the global movement patterns between various locations in an ambient assisted living environment (AAL) and the other dataset is associated with movement tracking using wearable sensing technologies.