Could In-Home Sensors Surpass Human Observation of People with Parkinson's at High Risk of Falling? An Ethnographic Study

Abstract

Self-report underpins our understanding of falls among people with Parkinson's (PwP) as they largely happen unwitnessed at home. In this qualitative study, we used an ethnographic approach to investigate which in-home sensors, in which locations, could gather useful data about fall risk. Over six weeks, we observed five independently mobile PwP at high risk of falling, at home. We made field notes about falls (prior events and concerns) and recorded movement with video, Kinect, and wearable sensors. The three women and two men (aged 71 to 79 years) having moderate or severe Parkinson's were dependent on others and highly sedentary. We most commonly noted balance protection, loss, and restoration during chair transfers, walks across open spaces and through gaps, turns, steps up and down, and tasks in standing (all evident walking between chair and stairs, e.g.). Our unobtrusive sensors were acceptable to participants: they could detect instability during everyday activity at home and potentially guide intervention. Monitoring the route between chair and stairs is likely to give information without invading the privacy of people at high risk of falling, with very limited mobility, who spend most of the day in their sitting rooms.

Figure 1

Summary of the data collection and analysis process.

Figure 2

Prototype inertial measurements logger (as worn (×5) by participants).

Figure 3

Example of Fall Map. Solid arrow shows a route through the kitchen-dining room that frequently challenges one participant; circles mark significant previous fall-events. A step between what were previously two rooms is less hazardous since the addition of grab rails on both sides. However, the participant relies on a heavy chair to provide additional support. Triangles mark camera positions.

Figure 4

Examples of people at high risk of falling “furniture creeping.” With or without walking aids, participants relied on the support of furniture to move safely across rooms and often appeared vulnerable in open space.

Figure 5

Examples of furniture obscuring the camera and challenging balance. Monitoring transfer into chairs and manoeuvring through gaps between furniture pieces would be informative as these activities frequently challenge balance. The obscured camera view highlights the importance of wearable devices as part of a sensor array.

Figure 6

Reliance on banisters and rails. Participants utilised every available support when tackling the stairs. In the absence of a banister on both sides of the stair case, one participant kept a hand on the stairlift track and one placed both hands on the one available rail.