2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication 2012
DOI: 10.1109/roman.2012.6343838
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Evaluation of wearable gyroscope and accelerometer sensor (PocketIMU2) during walking and sit-to-stand motions

Abstract: Recently healthcare of the elderly people has become a serious issue in medical and rehabilitation areas. In order to know their functional mobility and provide sufficient medical treatment, it is important to measure their body state precisely and objectively. Therefore we developed a wearable and wireless sensor of gyroscope and accelerometer (PocketIMU2) as an easy and precise measurement of human motions. In the sensor, we employed a small and high accurate LiNbO3 crystal to achieve joint angle computation… Show more

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Cited by 15 publications
(6 citation statements)
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References 7 publications
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“…Motion sensors, for example, accelerometers, gyroscopes, and magnetometers provide satisfactory data quality and reliability for the assessment of movement disorders. Moreover, they are affordable, necessarily miniaturized, and improve more rapidly compared to alternative devices usually used for movement assessment [ 67 , 68 ]. Their use ranges from observing functional motor movements, i.e., neuromuscular disorders (stroke and Parkinson’s disease) to the evaluation of physical activities to identify disease patterns for prevention, therapy, rehabilitation, and additionally, the assessment of changes in the movement of the newborn [ 26 , 27 , 67 , 68 ].…”
Section: Methodology Of the Reviewed Approachesmentioning
confidence: 99%
“…Motion sensors, for example, accelerometers, gyroscopes, and magnetometers provide satisfactory data quality and reliability for the assessment of movement disorders. Moreover, they are affordable, necessarily miniaturized, and improve more rapidly compared to alternative devices usually used for movement assessment [ 67 , 68 ]. Their use ranges from observing functional motor movements, i.e., neuromuscular disorders (stroke and Parkinson’s disease) to the evaluation of physical activities to identify disease patterns for prevention, therapy, rehabilitation, and additionally, the assessment of changes in the movement of the newborn [ 26 , 27 , 67 , 68 ].…”
Section: Methodology Of the Reviewed Approachesmentioning
confidence: 99%
“…What is more, the obtained data do not require further manual post-processing, which is quite common in visual MoCap solutions, for example due to marker occlusion and confusion. Research also proved that it is possible to obtain comparable accuracy of inertial sensors with respect to the optical MoCap system [ 47 , 48 ]. The disadvantage is the lack of direct position tracking (this is calculated by double integration of accelerometer data) [ 49 ], which might cause some amount of drift.…”
Section: Methodsmentioning
confidence: 99%
“…From the analysis of the state of the art in the design of automated modalities for the GUGT evaluation, a number of heterogeneous techniques and markerless joint estimation algorithms emerge. In [ 12 ], the authors propose the use of accelerometers and gyroscopes to measure the angles between hip, knee and ankle and to derive the corresponding temporal curves. The major drawbacks of this approach are the use of wearable sensors (with related acceptability issues by the subject) and the need for an initial calibration.…”
Section: Related Workmentioning
confidence: 99%