VAMP - a vision based sensor network for health care hygiene

Adequate hand-washing has been shown to be a critical activity in preventing the transmission of infections such as MRSA in health-care environments. Hand-washing guidelines published by various health-care related institutions recommend a technique incorporating six hand-washing poses that ensure all areas of the hands are thoroughly cleaned. In this paper, an embedded wireless vision system (VAMP) capable of accurately monitoring hand-washing quality is presented. The VAMP system hardware consists of a low resolution CMOS image sensor and FPGA processor which are integrated with a microcontroller and ZigBee standard wireless transceiver to create a wireless sensor network (WSN) based vision system that can be retargeted at a variety of health care applications. The device captures and processes images locally in real-time, determines if hand-washing procedures have been correctly undertaken and then passes the resulting high-level data over a low-bandwidth wireless link. The paper outlines the hardware and software mechanisms of the VAMP system and illustrates that it offers an easy to integrate sensor solution to adequately monitor and improve hand hygiene quality. Future work to develop a miniaturized, low cost system capable of being integrated into everyday products is also discussed.

A benchmark comparison between reconfigurable, intelligent and autonomous wireless inertial measurement and photonic technologies in rehabilitation

Advanced sensory systems address a number of major obstacles towards the provision for cost effective and proactive rehabilitation. Many of these systems employ technologies such as high-speed video or motion capture to generate quantitative measurements. However these solutions are accompanied by some major limitations including extensive set-up and calibration, restriction to indoor use, high cost and time consuming data analysis. Additionally many do not quantify improvement in a rigorous manner for example gait analysis for 5 minutes as opposed to 24 hour ambulatory monitoring. This work addresses these limitations using low cost, wearable wireless inertial measurement as a mobile and minimal infrastructure alternative. In cooperation with healthcare professionals the goal is to design and implement a reconfigurable and intelligent movement capture system. A key component of this work is an extensive benchmark comparison with the 'gold standard' VICON motion capture system.

A smart wireless inertial measurement unit system: simplifying & encouraging usage of WIMU technology

Wireless Inertial Measurement Units (WIMUs) combine motion sensing, processing & communications functionsin a single device. Data gathered using these sensors has the potential to be converted into high quality motion data. By outfitting a subject with multiple WIMUs full motion data can begathered. With a potential cost of ownership several orders of magnitude less than traditional camera based motion capture, WIMU systems have potential to be crucially important in supplementing or replacing traditional motion capture and opening up entirely new application areas and potential markets particularly in the rehabilitative, sports & at-home healthcarespaces. Currently WIMUs are underutilized in these areas. A major barrier to adoption is perceived complexity. Sample rates, sensor types & dynamic sensor ranges may need to be adjusted on multiple axes for each device depending on the scenario. As such we present an advanced WIMU in conjunction with a Smart WIMU system to simplify this aspect with 3 usage modes: Manual, Intelligent and Autonomous. Attendees will be able to compare the 3 different modes and see the effects of good andbad set-ups on the quality of data gathered in real time.