The project developed a remote hearing assessment system based on services on a web server. The system minimizes hardware and software requirements on the audiologist's computer and can be realized with regular Internet service subscription. Patient operations involved in hearing assessment are simple; making hearing test services more accessible to those otherwise may not be able to obtain the desired hearing care.
Photoplethysmographic (PPG) signals are easy to obtain with low cost, which enhances its potential to server as biometric identification mechanism for various applications. This paper examines two important issues in applying derivatives of PPG signals as discriminants to identify and verify subjects: consistency within an individual subject and discriminability between different subjects. The experimental results demonstrate that, by employing statistical tools, derivatives can precisely describe the features of an individual's PPG signal and be used as bio-measures for identification purposes.
The purpose of this research was to extend applications of the Internet and other telecommunication means to the assessment of hearing. The newly developed distributed system consists primarily of an application server and its database, and Web services under browser-server architecture to support remote hearing assessment. A pilot study was conducted: three independent audiologists assessed hearing of 25 subjects using testing approaches with different data communication configurations. Analysis of the results demonstrated the feasibility of replacing conventional "face-to-face" tests with the remote hearing tests using the distributed system. Because of its distributed architecture, the present system supports a new service model and separates technical maintenance and clinical services. Consequently, the system shows great potential to benefit the clinical hearing care profession. Future research is planned to apply this system to medical facilities and for distance applications.
Healthcare workers across the globe rely on medical gloves to prevent the transfer of harmful bacteria and viruses between themselves and their patients. Unfortunately, due to the lack of an in-use durability standard for medical gloves by the American Society for Testing and Materials, many of these gloves are of low quality and are easily torn or punctured, exposing wearers and patients to potentially deadly diseases. To solve this problem, a device that automatically detects material failures the size of a pinhole during active testing was invented. The device consists of a prosthetic hand, vacuum pump, mobile textured roller, pressure sensor, and liquid spray system. It works by creating a vacuum inside the glove and repeatedly moving the textured roller into contact with the fingertips, which, on the prosthetic hand, are porous. When a glove perforates, the vacuum is broken, pressure within the hand rapidly increases, and the operator is alerted on a touchscreen that the glove has failed. In addition, the liquid spray system allows the user to test gloves in “real world” conditions, because healthcare workers often come into contact with liquids that may alter glove durability. As a preliminary test of the device’s accuracy, five nitrile and five latex exam gloves were tested using the system’s default settings. Natural latex is known to be the highest performing glove material, so the nitrile gloves were expected to fail more quickly than the latex gloves. The test results concur with this expected order of failure: nitrile first, with an average failure time of 300 s and 42 average number of roller touches, followed by natural latex, with an average failure time of 2206 s and 300 average number of roller touches. These results provide evidence that the device accurately ranks glove durability, and therefore could be used to develop an ASTM durability standard and improve the quality of gloves made from different polymers.
Hand hygiene plays an important role in both healthcare institutions and food processing industries. This paper describes a tracking and localization method for hand hygiene activity monitoring. The localization algorithm was developed to identify different subjects with mobile tags within a predefined area near the hand-washing sink. A demo system was constructed that was comprised of a system server, one sink node, two anchor nodes and two mobile nodes. Preliminary tests were conducted. The collected data showed that the wearable mobile tag could be identified within a detectable area of 1.2m×0.7m in front of the hand-washing sink.
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