Non‐Intrusive Human Activity Radar System
![](/media-library/sites/red/images/commercialisation/3150_Non‐intrusive Human Activity Recognition.png)
A radar system for human detection that overcomes intrusion and privacy concerns associated with cameras.
Uses
- Geriatric population monitoring, including heart rate detection
- Human activity monitoring in low light or smoky environments
Benefits
- Less intrusive than current camera systems
- Low cost, high accuracy
- Operates in real-time
- Operates in any light condition, including at night, and in vapour, fog, steam, and smoke
![Two radars track human movement through a room, creating a diagram showing the range of human motion.](/media-library/sites/red/images/commercialisation/3150_HAR_diagram.png)
Human activity recognition (HAR) is used for monitoring people in environments such as care homes, hospitals, workplaces and lifts. Many HAR systems rely on cameras, sensors, wearable devices or a mixture thereof, to analyse human behaviour. The use of cameras raises privacy concerns and requires good lighting conditions.
Researchers from the University of Bristol have developed a HAR system using multiple millimetre-wave (mmWave) radars. These mmWave sensors are less intrusive and can detect speed, postures, movement direction and proximity in a far broader range of light conditions than the current state-of-the-art camera systems.
Other available technologies
See below for more technologies developed at the University of Bristol
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Human Podocyte Cell Line
A conditionally immortalised human podocyte cell line. It is a unique and representative tool for the study of human glomerular disease.
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Real-time dose verification in radiotherapy
A team from the Universities of Bristol and Swansea together with University Hospitals Bristol NHS Foundation Trust has developed a novel radiation detector device for determining the dose from Intensity Modulated Radiotherapy (IMRT) in real-time.
Real-Time Short-Range Human Posture Estimation Using mmWave Radars and Neural Networks
In this paper, Dr. Naim Dahnoun presents a novel human posture estimation system using Millimetre-wave (mmWave) radar. The system's high resolution, non-intrusive nature and suitability for a variety of environments have made it an increasingly popular option for human activity recognition.
Professor Naim Dahnoun
Professor Naim Dahnoun is a Professor of Teaching and Learning in Signal Processing in the School of Electrical, Electronic and Mechanical Engineering at the University of Bristol.