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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2022,9,6]]},"abstract":"<jats:p>We propose MiShape, a millimeter-wave (mmWave) wireless signal based imaging system that generates high-resolution human silhouettes and predicts 3D locations of body joints. The system can capture human motions in real-time under low light and low-visibility conditions. Unlike existing vision-based motion capture systems, MiShape is privacy non-invasive and can generalize to a wide range of motion tracking applications at-home. To overcome the challenges with low-resolution, specularity, and aliasing in images from Commercial-Off-The-Shelf (COTS) mmWave systems, MiShape designs deep learning models based on conditional Generative Adversarial Networks and incorporates the rules of human biomechanics. We have customized MiShape for gait monitoring, but the model is well adaptive to any tracking applications with limited fine-tuning samples. We experimentally evaluate MiShape with real data collected from a COTS mmWave system for 10 volunteers, with diverse ages, gender, height, and somatotype, performing different poses. Our experimental results demonstrate that MiShape delivers high-resolution silhouettes and accurate body poses on par with an existing vision-based system, and unlocks the potential of mmWave systems, such as 5G home wireless routers, for privacy-noninvasive healthcare applications.<\/jats:p>","DOI":"10.1145\/3550300","type":"journal-article","created":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T14:54:27Z","timestamp":1662562467000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["MiShape"],"prefix":"10.1145","volume":"6","author":[{"given":"Aakriti","family":"Adhikari","sequence":"first","affiliation":[{"name":"University of South Carolina, USA"}]},{"given":"Hem","family":"Regmi","sequence":"additional","affiliation":[{"name":"University of South Carolina, USA"}]},{"given":"Sanjib","family":"Sur","sequence":"additional","affiliation":[{"name":"University of South Carolina, USA"}]},{"given":"Srihari","family":"Nelakuditi","sequence":"additional","affiliation":[{"name":"University of South Carolina, USA"}]}],"member":"320","published-online":{"date-parts":[[2022,9,7]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Networking and Services on 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services","author":"Yao Lina","year":"2015","unstructured":"Yao, Lina and Sheng, Quan Z. and Ruan, Wenjie and Gu, Tao and Li, Xue and Falkner, Nick and Yang, Zhi, \"RF-Care: Device-Free Posture Recognition for Elderly People Using A Passive RFID Tag Array,\" in Proceedings of the 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services on 12th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2015."},{"key":"e_1_2_1_2_1","volume-title":"A Literature Survey,\" Frontiers in Robotics and AI","author":"Wang Xueyi","year":"2020","unstructured":"Wang, Xueyi and Ellul, Joshua and Azzopardi, George, \"Elderly Fall Detection Systems: A Literature Survey,\" Frontiers in Robotics and AI, vol. 7, 2020."},{"key":"e_1_2_1_3_1","first-page":"10","article-title":"Mobile Health Technology for Remote Home Monitoring After Surgery: A Meta-Analysis","volume":"21","author":"Dawes A J","year":"2021","unstructured":"Dawes, A J and Lin, A Y and Varghese, C and Russell, M M and Lin, A Y, \"Mobile Health Technology for Remote Home Monitoring After Surgery: A Meta-Analysis,\" British Journal of Surgery, vol. 21, 10 2021.","journal-title":"British Journal of Surgery"},{"key":"e_1_2_1_4_1","volume-title":"2017 IEEE International Conference on Mechatronics and Automation (ICMA)","author":"Ghazi Mustafa A","year":"2017","unstructured":"Ghazi, Mustafa A. and Ding, Lei and Fagg, Andrew H. and Kolobe, Thubi H.A. and Miller, David P., \"Vision-Based Motion Capture System for Tracking Crawling Motions of Infants,\" in 2017 IEEE International Conference on Mechatronics and Automation (ICMA), 2017."},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Anh L. 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