Proceedings of the 2017 International Conference on Digital Health
Muckell, Jonathan, Yuchi Young, and Mitch Leventhal
Patients with functional disabilities often require assistance to perform basic everyday activities, such as bathing, dressing, and getting into/out of bed. These activities typically require the direct care worker (DCW) to transfer (lift & move) the patient from one location to another. These patient transfers are a common cause of injury to health care workers. In fact, depending on the job site, on average a staggering 4% of DCWs are injured every year. Following proper lifting and transfer procedures can dramatically reduce the risk of injury. This research demonstrates that data collected from motion tracking systems, combined with computational analysis can detect risky patient transfer behavior. Testing of the system occurred as part of an exploratory study in an assisted living facility. Two common types of transfers were tested: transfers from bed to shower chair, and transfers from shower chair to wheelchair. These scenarios were tested on two types of patients, one that was completely disabled, and one that was partially disabled. Two major results were determined from this study: (1) risky patient transfer behavior is common in the assisted living facility, and (2) this behavior can be adequately detected via wearable motion tracking sensors. The longer term research goal is to extend these preliminary results to construct a fully wearable motion tracking system that can be used as a tool to reinforce proper lifting and transfer protocols to reduce work-related injuries among DCWs.
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