Validation of noninvasive body sensor network technology in the detection of agitation in dementia.

OBJECTIVE: Agitated behaviors are one of the most frequent reasons that patients with dementia are placed in long-term care settings. This study aims to validate the ability of a custom Body Sensor Network (BSN) to capture the presence of agitation against currently accepted subjective measures, the Cohen-Mansfield Agitation Inventory (CMAI) and the Aggressive Behavior Scale (ABS) and to discriminate between agitation and cognitive decline. METHODS: Six patients identified as being at high risk for agitated behaviors were enrolled in this study. The devices were applied at three sites for three hours while behaviors were annotated simultaneously and subsequently repeated twice for each enrolled subject. RESULTS: We found that the BSN was a valid measure of agitation based on construct validity testing and secondary validation using non-parametric ANOVAs. DISCUSSION: The BSN shows promise from these pilot results. Further testing with a larger sample is needed to replicate these results.

Portable, Non-Invasive Fall Risk Assessment in End Stage Renal Disease Patients on Hemodialysis.

Patients with end stage renal diseases (ESRD) on hemodialysis (HD) have high morbidity and mortality due to multiple causes, one of which is dramatically higher fall rates than the general population. The mobility mechanisms that contribute to falls in this population must be understood if adequate interventions for fall prevention are to be achieved. This study utilizes emerging non-invasive, portable gait, posture, strength, and stability assessment technologies to extract various mobility parameters that research has shown to be predictive of fall risk in the general population. As part of an ongoing human subjects study, mobility measures such as postural and locomotion profiles were obtained from five (5) ESRD patients undergoing HD treatments. To assess the effects of post-HD-fatigue on fall risk, both the pre- and post-HD measurements were obtained. Additionally, the effects of inter-HD periods (two days vs. three days) were investigated using the non-invasive, wireless, body-worn motion capture technology and novel signal processing algorithms. The results indicated that HD treatment influenced strength and mobility (i.e., weaker and slower after the dialysis, increasing the susceptibility to falls while returning home) and inter-dialysis period influenced pre-HD profiles (increasing the susceptibility to falls before they come in for a HD treatment). Methodology for early detection of increased fall risk - before a fall event occurs - using the portable mobility assessment technology for out-patient monitoring is further explored, including targeting interventions to identified individuals for fall prevention.