mlsanityData to 14 Oct 2026

Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey

arXiv 2004.08821 ↗First posted 19 Apr 2020eess.SP cs.HC cs.LGcited by 26

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Abstract (arXiv)

In the last decade, Human Activity Recognition (HAR) has become a vibrant research area, especially due to the spread of electronic devices such as smartphones, smartwatches and video cameras present in our daily lives. In addition, the advance of deep learning and other machine learning algorithms has allowed researchers to use HAR in various domains including sports, health and well-being applications. For example, HAR is considered as one of the most promising assistive technology tools to support elderly's daily life by monitoring their cognitive and physical function through daily activities. This survey focuses on critical role of machine learning in developing HAR applications based on inertial sensors in conjunction with physiological and environmental sensors.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Apr 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 3; 2022: 4; 2023: 7; 2024: 3; 2025: 6; 2026: 3.

26 papers.

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  1. 2023Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensorscited by 11
  2. 2022Progressive Cross-modal Knowledge Distillation for Human Action Recognitioncited by 6
  3. 2021B-HAR: an open-source baseline framework for in depth study of human activity recognition datasets and workflowscited by 4
  4. 2025Scaling laws in wearable human activity recognitioncited by 4
  5. 2021Estimating indoor occupancy through low-cost BLE devicescited by 3
  6. 2025HAROOD: A Benchmark for Out-of-distribution Generalization in Sensor-based Human Activity Recognitioncited by 3
  7. 2026Inertia-1: An Open Exploration of Wearable Motion Foundation Modelscited by 3
  8. 2022Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognitioncited by 2
  9. 2023MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Predictioncited by 2
  10. 2023A Comprehensive Review of Automated Data Annotation Techniques in Human Activity Recognitioncited by 2
  11. 2024SoK: Behind the Accuracy of Complex Human Activity Recognition Using Deep Learningcited by 2
  12. 2025CNN Autoencoders for Hierarchical Feature Extraction and Fusion in Multi-sensor Human Activity Recognitioncited by 2
14 more
  1. 2021WaveGlove: Transformer-based hand gesture recognition using multiple inertial sensorscited by 1
  2. 2023A Survey on Multi-Resident Activity Recognition in Smart Environmentscited by 1
  3. 2023A Multi-Stage Temporal Convolutional Network for Volleyball Jumps Classification Using a Waist-Mounted IMUcited by 1
  4. 2025LLM-Guided Exemplar Selection for Few-Shot Wearable-Sensor Human Activity Recognitioncited by 1
  5. 2022Latent Space Unsupervised Semantic Segmentationcited by 0
  6. 2022Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognitioncited by 0
  7. 2023rWISDM: Repaired WISDM, a Public Dataset for Human Activity Recognitioncited by 0
  8. 2023Game Theory Solutions in Sensor-Based Human Activity Recognition: A Reviewcited by 0
  9. 2024Elevator, Escalator, or Neither? Classifying Conveyor State Using Smartphone under Arbitrary Pedestrian Behaviorcited by 0
  10. 2024ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based Human Activity Recogntioncited by 0
  11. 2025Classification Filteringcited by 0
  12. 2025Human Activity Recognition Based on Electrocardiogram Data Onlycited by 0
  13. 2026WHAR Arena: Benchmarking the State of the Art in Efficient Wearable Human Activity Recognitioncited by 0
  14. 2026From Compression to Deployment: Real-Time and Energy-Efficient FastGRNN on Ultra-Constrained Microcontrollerscited by 0