IEEE Internet of Things Journal · 2020 · 35 citations · 38 references
EducationPhysical EducationAssistive TechnologyMovement AnalysisPhysical ActivityExercise TherapyFitness AssessmentGesture AnalysisPhysical FitnessStrength TrainingWearable Health TechnologiesAccuracyActivity MonitoringGesture SensingGesture-based InterfacesPhysical Activity MonitoringReal-time MonitoringReal-time ProcessingUser-dependent Gesture Recognition
Strength training is becoming increasingly popular among all age groups, as it helps the participants increase muscle strength, improve body flexibility, reduce health risks, and reshape physical forms. However, strength training imposes strict regulations on gestures and requires professional instruction in real time for the sake of body-building efficiency and safety. For this purpose, in this article, we propose a novel low-cost system named iCoach, to provide real-time monitoring and coaching service for strength training participants. Specifically, we design and implement a smart fitness glove, which can be seamlessly equipped with a pervasive inertial unit. With this customized but low-cost device, we can recognize various training programs, detect nonstandard behaviors while exercising, and assess exercising qualities of a user. Our primary experimental results show that iCoach can recognize 15 sets of training programs, detect three common nonstandard behaviors, and assess the quality of training with high accuracy and reliability.
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Whole-home gesture recognition using wireless signals
Qifan Pu, Sidhant Gupta, Shyamnath Gollakota et al. · 2013 · 1.1K citations
Essentials of Strength Training and Conditioning
Nicola Phillips · Physiotherapy · 1997 · 1.1K citations
Education, Kinesiology, Physiology +12
Understanding and Modeling of WiFi Signal Based Human Activity Recognition
Wei Wang, Alex X. Liu, Muhammad Shahzad et al. · 2015 · 1.1K citations