Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey
Sizhen Bian, Mengxi Liu, Bo Zhou, Paul Lukowicz, Michele Magno
Abstract
Due to the fact that roughly sixty percent of the human body is essentially composed of water, the human body is inherently a conductive object, being able to, firstly, form an inherent electric field from the body to the surroundings and secondly, deform the distribution of an existing electric field near the body. Body-area capacitive sensing, also called body-area electric field sensing, is becoming a promising alternative for wearable devices to accomplish certain tasks in human activity recognition (HAR) and human-computer interaction (HCI). Over the last decade, researchers have explored plentiful novel sensing systems backed by the body-area electric field, like the ring-form smart devices for sign language recognition, the room-size capacitive grid for indoor positioning, etc. On the other hand, despite the pervasive exploration of the body-area electric field, a comprehensive survey does not exist for an enlightening guideline. Moreover, the various hardware implementations, applied algorithms, and targeted applications result in a challenging task to achieve a systematic overview of the subject. This paper aims to fill in the gap by comprehensively summarizing the existing works on body-area capacitive sensing so that researchers can have a better view of the current exploration status. To this end, we first sorted the explorations into three domains according to the involved body forms: body-part electric field, whole-body electric field, and body-to-body electric field, and enumerated the state-of-art works in the domains with a detailed survey of the backed sensing tricks and targeted applications. We then summarized the three types of sensing frontends in circuit design, which is the most critical part in body-area capacitive sensing, and analyzed the data processing pipeline categorized into three kinds of approaches. The outcome will benefit researchers for further body-area electric field explorations. Finally, we described the challenges and outlooks of body-area electric sensing, followed by a conclusion, aiming to encourage researchers to further investigations considering the pervasive and promising usage scenarios backed by body-area capacitive sensing.
• Computing methodologies → Neural networks; Knowledge representation and reasoning.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext d5cdfd94-c38a-4aff-b61f-4552100be5fbCited by top-tier papers2
- SeamPose: Repurposing Seams as Capacitive Sensors in a Shirt for Upper-Body Pose TrackingTianhong Catherine Yu, Manru Mary Zhang, Peter He, Chi-Jung Lee et al.UIST 2024 · 16 citations
- Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And OutlookSizhen Bian, Mengxi Liu, Lala Shakti Swarup Ray, Bo Zhou et al.UbiComp 2026 · 2 citations
Builds on8
- Once-for-All: Train One Network and Specialize it for Efficient DeploymentHan Cai, Chuang Gan, Tianzhe Wang, Zhekai Zhang et al.ICLR 2020 · 1,522 citations
- On-Device Training Under 256KB MemoryJi Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang et al.NeurIPS 2022 · 345 citations
- BodyCompass: Monitoring Sleep Posture with Wireless SignalsShichao Yue, Yuzhe Yang, Hao Wang, Hariharan Rahul et al.UbiComp 2020 · 112 citations
- EFRing: Enabling Thumb-to-Index-Finger Microgesture Interaction through Electric Field Sensing Using Single Smart RingTaizhou Chen, Tianpei Li, Xingyu Yang, Kening ZhuUbiComp 2023 · 51 citations
- LT-Fall: The Design and Implementation of a Life-threatening Fall Detection and Alarming SystemDuo Zhang, Xusheng Zhang, Shengjie Li, Yaxiong Xie et al.UbiComp 2023 · 49 citations
Related papers
- DancingAnt: Body-empowered Wireless Sensing Utilizing Pervasive Radiations from PowerlineMinhao Cui, Binbin Xie, Qing Wang, Jie XiongMobiCom 2023 · 6 citations
- EVLeSen: In-Vehicle Sensing with EV-Leaked SignalMinhao Cui, Binbin Xie, Qing Wang, Jie XiongMobiCom 2024 · 8 citations
- Unsupervised Human Activity Representation Learning with Multi-task Deep ClusteringHaojie Ma, Zhijie Zhang, Wenzhong Li, Sanglu LuUbiComp 2021 · 46 citations
- SenseCollect: We Need Efficient Ways to Collect On-body Sensor-based Human Activity Data!Wenqiang Chen, Shupei Lin, Elizabeth Thompson, John A. StankovicUbiComp 2021 · 34 citations
- Contrastive Predictive Coding for Human Activity RecognitionHarish Haresamudram, Irfan A. Essa, Thomas PlötzUbiComp 2021 · 149 citations
