2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2016
DOI: 10.1109/bsn.2016.7516256
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A software assistant for user-centric calibration of a wireless body sensor

Abstract: Abstract-Body sensors have a promising contribution to health promotion in many areas of daily life (telemedicine, corporate health care or recreational sports). However, the valid measurement of vital signs and kinematic data strongly depends on the signals' quality and the users' compliance (proper usage). Although, there is a lot of research work concerning accuracy and calibration of wireless body sensors the human user is typically not involved. Thus, in this work, we present a software assistant (wizard)… Show more

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Cited by 2 publications
(1 citation statement)
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References 16 publications
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“…Physical activity recognition 17 --10 7 -- [8] Physical activity recognition 14 ------ [9] Physical activity recognition 4 - For completeness, the remaining 13 articles not listed in Table 2 and 3 were distributed over eight article categories: Asthma/COPD [63], Cardiovascular diseases [64], Gait and fall [65][66][67], Neurological diseases [68], Physical activity recognition [69], Rehabilitation [70], Stress and sleep [71], and Additional [72][73][74][75]. Six articles report on systems where studies are upcoming [63,64,[72][73][74][75]. One of them [64] is a continuation of the study reported in [23].…”
Section: Qualitative Synthesismentioning
confidence: 99%
“…Physical activity recognition 17 --10 7 -- [8] Physical activity recognition 14 ------ [9] Physical activity recognition 4 - For completeness, the remaining 13 articles not listed in Table 2 and 3 were distributed over eight article categories: Asthma/COPD [63], Cardiovascular diseases [64], Gait and fall [65][66][67], Neurological diseases [68], Physical activity recognition [69], Rehabilitation [70], Stress and sleep [71], and Additional [72][73][74][75]. Six articles report on systems where studies are upcoming [63,64,[72][73][74][75]. One of them [64] is a continuation of the study reported in [23].…”
Section: Qualitative Synthesismentioning
confidence: 99%