Simulated Unobtrusive Falls Detection With Multiple Persons

Abstract

One serious issue related to falls among the elderly living at home or in a residential care facility is the "long lie" scenario, which involves being unable to get up from the floor after a fall for 60 min or more. This research uses a simulated environment to investigate the potential effectiveness of using wireless ambient sensors (dual-technology (microwave/infrared) motion detectors and pressure mats) to track the movement of multiple persons and to unobtrusively detect falls when they occur, therefore reducing the rate of occurrence of "long lie" scenarios. A path-finding algorithm (A*) is used to simulate the movement of one or more persons through the residential area. For analysis, the sensor network is represented as an undirected graph, where nodes in the graph represent sensors, and edges between nodes in the graph imply that these sensors share an overlapping physical region in their area of sensitivity. A second undirected graph is used to represent the physical adjacency of the sensors (even where they do not overlap in their monitored regions). These graphical representations enable the tracking of multiple subjects/groups within the environment, by analyzing the sensor activation and adjacency profiles, hence allowing individuals/groups to be isolated when multiple persons are present, and subsequently monitoring falls events. A falls algorithm, based on a heuristic decision tree classifier model, was tested on 15 scenarios, each including one or more persons; three scenarios of activity of daily living, and 12 different types of falls (four types of fall, each with three postfall scenarios). The sensitivity, specificity, and accuracy of the falls algorithm are 100.00%, 77.14%, and 89.33%, respectively.

Design of an unobtrusive system for fall detection in multiple occupancy residences

“…This algorithm was seen to be improved by incorporating two motion sensors to monitor the upper and lower parts of the room [16]. Listed results show a sensitivity of 100.00% and an accuracy of 87.33% for simulated scenarios involving an older person living with one or two family members, when using the upper and lower sensors.…”

“…The long lie event could be recognized by the system when only sensors monitoring the lower part of room responded to movement of the fallen but conscious individual, while unconscious falls could be identified by the system when all sensors in the room were deactivated. It means that the trial results can be further improved by adapting the proposed system from [16] for the future implementation.…”

“…• Active sensors at the current time are grouped into "cliques" based on whether all the sensor activations in the clique (more detailed information can be found in [16]) are attributable to a person or a group of persons. • At successive time steps, cliques are split, paired or merged, since individuals may walk as a group and then move in different directions as individuals, or move as an individual and subsequently merge into a group.…”

“…Preliminary work on this topic by our group has focused on the use of a wireless sensor network (WSN) software simulator to generate sensor signals, which may be considered as mimicking the real sensor signals from a subject performing certain activities, and the development of an algorithm to distinguish between falls and other activities during the day in a house with multiple residents [16]. In our simulation, the motion sensor was assumed to have a perfect detection 35th Annual International Conference of the IEEE EMBS Osaka, Japan, 3 -7 July, 2013 of the moving objects.…”

Challenges and Issues in Multisensor Fusion Approach for Fall Detection: Review Paper

“…At he same time their operation capabilities are highly limited by the area of distribution. Typically sensors involved in the context-aware monitoring are represented by cameras [24], vibration sensors [27], sound detector [26], pressure mats [29], and floor or infrared sensors [28]. Table 2 gives an overview of the most significant studies in this area.…”