Physical performance measures predict health and function in older populations. Walking speed in particular has consistently predicted morbidity and mortality. However, single brief walking measures may not reflect a person’s typical ability. Using a system that unobtrusively and continuously measures walking activity in a person’s home we examined walking speed metrics and their relation to function. In 76 persons living independently (mean age, 86) we measured every instance of walking past a line of passive infra-red motion sensors placed strategically in their home during a four-week period surrounding their annual clinical evaluation. Walking speeds and the variance in these measures were calculated and compared to conventional measures of gait, motor function and cognition. Median number of walks per day was 18 ± 15. Overall mean walking speed was 61 ± 17 cm/sec. Characteristic fast walking speed was 96 cm/sec. Men walked as frequently and fast as women. Those using a walking aid walked significantly slower and with greater variability. Morning speeds were significantly faster than afternoon/evening speeds. In-home walking speeds were significantly associated with several neuropsychological tests as well as tests of motor performance. Unobtrusive home walking assessments are ecologically valid measures of walking function. They provide previously unattainable metrics (periodicity, variability, range of minimum and maximum speeds) of everyday motor function.

Gait velocity has been shown to quantitatively estimate risk of future hospitalization, has been shown to be a predictor of disability, and has been shown to slow prior to cognitive decline. In this paper, we describe a system for continuous and unobtrusive in-home assessment of gait velocity, a critical metric of function. This system is based on estimating walking speed from noisy time and location data collected by a "sensor line" of restricted view passive infrared (PIR) motion detectors. We demonstrate the validity of our system by comparing with measurements from the commercially available GAITRite® Walkway System gait mat. We present the data from 882 walks from 27 subjects walking at three different subject-paced speeds (encouraged to walk slowly, normal speed, or fast) in two directions through a sensor line. The experimental results show that the uncalibrated system accuracy (average error) of estimated velocity was 7.1cm/s (SD = 11.3cm/s), which improved to 1.1cm/s (SD = 9.1cm/s) after a simple calibration procedure. Based on the average measured walking speed of 102 cm/s our system had an average error of less than 7% without calibration and 1.1% with calibration.

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Introduction Subtle changes in cognitively demanding activities occur in MCI but are difficult to assess with conventional methods. In an exploratory study, we examined whether patterns of computer mouse movements obtained from routine home computer use discriminated between older adults with and without MCI. Methods Participants were 42 cognitively intact and 20 older adults with MCI enrolled in a longitudinal study of in-home monitoring technologies. Mouse pointer movement variables were computed during one week of routine home computer use using algorithms that identified and characterized mouse movements within each computer use session. Results MCI was associated with making significantly fewer total mouse moves (p<.01), and making mouse movements that were more variable, less efficient, and with longer pauses between movements (p<.05). Mouse movement measures were significantly associated with several cognitive domains (p’s<.01–.05). Discussion Remotely monitored computer mouse movement patterns are a potential early marker of real-world cognitive changes in MCI.