Telesurveillance of elderly patients by use of passive infra-red sensors in a 'smart' room

Abstract

We have developed an automated surveillance system based on passive infra-red sensors. Eight sensors were installed in a hospital room. A computer automatically captured data from the sensors every night from 21:00 until 06:00 the following morning. The sensors were polled twice per second and when a sensor was activated by movement, the event and time were recorded in a data file. At the end of the surveillance period the program analysed the data and generated a report showing the activities taking place in the room and their times. Four elderly patients were observed for a total of 97 nights. A total of 1637 possible sequences of movements by the patient and the hospital staff were detected. The computer was able to identify 1450 sequences (89%) correctly, in comparison with manual analysis. Only 10 movements (0.6%) were undetected by the system; all were very short sequences (five or six activations of the sensors). The system was generally capable of detecting and classifying all major movements in the room.

Unobtrusive and Ubiquitous In-Home Monitoring: A Methodology for Continuous Assessment of Gait Velocity in Elders

“…For example, passive infrared sensors have been used in-home for the estimation of amount [4] and type [5] of daily activity and in-hospital for classification of patient movements [6]. Other systems have been proposed that detect falls in elders [7], infer activities of daily living (ADLs) [8], use computer interactions to detect cognitive changes [9], and for continuous and unobtrusive in-home behavioral monitoring [10].…”

On the disambiguation of passively measured in-home gait velocities from multi-person smart homes

“…Many groups have employed PIR sensors in smart environments either alone or with other sensors to instrument the environment passively in order to monitor behavioral patterns attempting to infer activities or behaviors (for example, [2, 19, 30]). In the Intelligent Systems for Assessing Aging Changes (ISAAC) study [23], we have deployed an average of 11 PIR motion sensors per home (in addition to between 1–3 contact sensors monitoring doors and refrigerators) as part of an in-home monitoring network designed to detect functional and cognitive decline early and to support aging-in-place for elders.…”

Measurement of Neuropsychiatric Symptoms in Clinical Trials Targeting Alzheimer's Disease and Related Disorders

“…Automated surveillance system based on passive infra-red sensors has been developed [49] and shown ability to identify correctly 89% sequences of movement, in comparison with manual analysis.…”