# Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey

arXiv: https://arxiv.org/abs/2401.06000 · HTML: https://mlsanity.com/paper/2401.06000/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 175 references that are in the map.
- First posted on arXiv 11 Jan 2024.

## Builds on (most cited first, 12 of 12)

- [Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding](https://mlsanity.com/paper/1510.00149/) (2015)
- [Once-for-All: Train One Network and Specialize it for Efficient Deployment](https://mlsanity.com/paper/1908.09791/) (2019)
- [Deep Facial Expression Recognition: A Survey](https://mlsanity.com/paper/1804.08348/) (2018)
- [Online Learning: A Comprehensive Survey](https://mlsanity.com/paper/1802.02871/) (2018)
- [On-Device Training Under 256KB Memory](https://mlsanity.com/paper/2206.15472/) (2022)
- [TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device Learning](https://mlsanity.com/paper/2007.11622/) (2020)
- [Tiny Machine Learning for Concept Drift](https://mlsanity.com/paper/2107.14759/) (2021)
- [The Contribution of Human Body Capacitance/Body-Area Electric Field To Individual and Collaborative Activity Recognition](https://mlsanity.com/paper/2210.14794/) (2022)
- [Non-contact, real-time eye blink detection with capacitive sensing](https://mlsanity.com/paper/2211.05541/) (2022)
- [Tracking Human Pose During Robot-Assisted Dressing using Single-Axis Capacitive Proximity Sensing](https://mlsanity.com/paper/1709.07957/) (2017)
- [CoughTrigger: Earbuds IMU Based Cough Detection Activator Using An Energy-efficient Sensitivity-prioritized Time Series Classifier](https://mlsanity.com/paper/2111.04185/) (2021)
- [High-Sensitivity Electric Potential Sensors for Non-Contact Monitoring of Physiological Signals](https://mlsanity.com/paper/2110.12313/) (2021)

## Abstract (arXiv)

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 and human-computer interaction. Over the last decade, researchers have explored plentiful novel sensing systems backed by the body-area electric field. 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. Finally, we described the challenges and outlooks of body-area electric sensing.