2020
DOI: 10.1007/978-981-15-5679-1_51
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Human Activity Recognition Using Wearable Sensors

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Cited by 8 publications
(4 citation statements)
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“…Gravity sensors are usually used to determine the relative orientation of the device in space [33]- [35]. A gyroscope measures orientation based on angular momentum [18], [29], [36], [37].…”
Section: Data Collectionmentioning
confidence: 99%
“…Gravity sensors are usually used to determine the relative orientation of the device in space [33]- [35]. A gyroscope measures orientation based on angular momentum [18], [29], [36], [37].…”
Section: Data Collectionmentioning
confidence: 99%
“…Even though machine‐learning methods functioned effectively in wearable sensor activity recognition, the need to achieve state‐of‐the‐art and address the relative bottlenecks of the machine learning approach has led to the adoption of deep learning for wearable sensor activity recognition. Deep learning has been successful in a variety of fields such as image segmentation, 30 image feature extraction, 31 classification, 32 object detection, 33 and sentiment analysis, 34 among other areas. Deep learning models are generally capable of extracting features from wearable sensor datasets automatically 14 since it enables the model to learn all layers of representation jointly at the same time.…”
Section: Related Workmentioning
confidence: 99%
“…Health issues are eventually the crucial issues that encourage research to conduct research in human activity recognition. Studies for healthcare can be observed in [1,2,3,4,51]. This proposed MEDIC, a medical diagnosis and patient monitoring system designed by using physiological body worn and wireless contextual sensors network [2].…”
Section: Introductionmentioning
confidence: 99%