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This paper presents a representative use case of mHealth. The use case, called patient monitoring, is described from a Mobile Network Operator (MNO) point of view and should be seen as complimentary to other use cases that already exist from other parts of the industry. Then three communication scenarios are abstracted form the use case in order to clarify(More)
This paper introduces a novel hearing aid named artificial ultrasonic bone conduction hearing device, which is different from the traditional hearing aid in two sides: 1) sound conduction manner, 2) human perceptive principles. We focus on discussing the structure of the hearing aid and the research of frequency transposition algorithm. In addition, we(More)
In order to make the artificial forearm controller easier be trained and have higher robust, an adaptive controller for myoelectric signal (MES) is proposed. The control signal, MES, is derived from natural contraction patterns, which can be produced reliably with no subject training. To find features of MES, twenty-five filters with different center(More)
This paper describes E-Health Monitoring (EHM) ecosystem and current EHM market segments. Based on IoT reference model, three EHM technical models are proposed. Model 1 focuses on device to device communication; model 2 focuses on network providing connection only; model 3 focuses on network combined with platform. Model 3 is equipped with a service support(More)
Effective feature extraction is vital to reliable classification. To improve the accuracy of transient myoelectric signal (MES) pattern classification, a group of filter based time-series representation is proposed. Twenty-five filters with the same bandwidth but different center frequency divide the signal frequency spectrum into 25 sub-bands. It is shown(More)
Based on software radio theory, this paper focuses on researching a direct conversion structure for the radio frequency (RF) receiver front-end and tries to apply this flexible receiver front-end in MRI receiving system. In particular, we look at the conventional architecture of RF receiver front-ends of MRI; present architecture of a direct conversion for(More)
Six Chinese vowels /a/, /o/, /e/, /i/, /u/, and /u/ are recognized based on the one-channel detected facial myoelectric signal (MES). Zygomaticus major and anterior belly of the digastric are carefully selected as the electrodes sites of MES detected. Over-sampling technology and four-layer wavelet decomposition are used to reduce noise in MES records.(More)
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