Hardware Deployable Edge AI Solution for Posture Classification Using mmWave Radar and Low- Computational Machine Learning Model

• Published in: IEEE sensors journal Vol. 24; no. 16; pp. 26836 - 26844
• Main Authors: Pratap Singh, Yash, Gupta, Aham, Chaudhary, Devansh, Wajid, Mohd, Srivastava, Abhishek, Mahajan, Pranjal
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.08.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Artificial Intelligence (AI); Chirp; Classification; Continuous radiation; Datasets; Hardware; Machine learning; millimeter wave (mmWave); Millimeter wave communication; Millimeter waves; point-cloud images; Posture; posture classification; Privacy; Radar; Radar data; Radar imaging; Sensors; Spatial data; Three dimensional models; Three-dimensional displays; tiny machine learning

Identifying correct human postures is crucial in areas, such as patient care, in hospitals. However, the traditional vision-based methods widely used for this purpose raise privacy concerns for the subject, and the other wearable sensor-based approaches are impractical for real-world scenarios. In t...