5 research outputs found

    Presence Detection with Bluetooth Low Energy: A Review and Experiment

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    Bluetooth is one of the most ubiquitous technologies in smart phone today and its prominence in other devices is rising rapidly. It has become the De Facto technology used when there is need for device-to-device communication. However, the evolving standard has much more to offer. Bluetooth can power many applications due to capabilities. A key metric of Bluetooth is the Received Signal Strength Indicator (RSSI) and depending on the readings one can infer locality. This study evaluates existing research that attempts localization implemented using the Bluetooth protocol and the metrics that power those applications. A proof-of-concept software is developed to further investigate the feasibility of presence detection using Bluetooth Low Energy without connection to a device.&nbsp

    Evaluation of a clinical decision support tool for osteoporosis disease management: protocol for an interrupted time series design

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    <p>Abstract</p> <p>Background</p> <p>Osteoporosis affects over 200 million people worldwide at a high cost to healthcare systems. Although guidelines on assessing and managing osteoporosis are available, many patients are not receiving appropriate diagnostic testing or treatment. Findings from a systematic review of osteoporosis interventions, a series of mixed-methods studies, and advice from experts in osteoporosis and human-factors engineering were used collectively to develop a multicomponent tool (targeted to family physicians and patients at risk for osteoporosis) that may support clinical decision making in osteoporosis disease management at the point of care.</p> <p>Methods</p> <p>A three-phased approach will be used to evaluate the osteoporosis tool. In phase 1, the tool will be implemented in three family practices. It will involve ensuring optimal functioning of the tool while minimizing disruption to usual practice. In phase 2, the tool will be pilot tested in a quasi-experimental interrupted time series (ITS) design to determine if it can improve osteoporosis disease management at the point of care. Phase 3 will involve conducting a qualitative postintervention follow-up study to better understand participants' experiences and perceived utility of the tool and readiness to adopt the tool at the point of care.</p> <p>Discussion</p> <p>The osteoporosis tool has the potential to make several contributions to the development and evaluation of complex, chronic disease interventions, such as the inclusion of an implementation strategy prior to conducting an evaluation study. Anticipated benefits of the tool may be to increase awareness for patients about osteoporosis and its associated risks and provide an opportunity to discuss a management plan with their physician, which may all facilitate patient self-management.</p
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