Smart Multi-Sensor Wristband for Gesture Classification 14 th Nov - PowerPoint PPT Presentation

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Smart Multi-Sensor Wristband for Gesture Classification 14 th Nov 2019 Yuchi Liu and Rami Ghannam Microelectronics Lab (meLAB) www.melabresearch.com School of Engineering, University of Glasgow G12 8QQ, Scotland, UK 2109504L@student.gla.ac.uk

Smart Multi-Sensor Wristband for Gesture Classification 14 th Nov 2019 Yuchi Liu and Rami Ghannam Microelectronics Lab (meLAB) www.melabresearch.com School of Engineering, University of Glasgow G12 8QQ, Scotland, UK 2109504L@student.gla.ac.uk rami.ghannam@glasgow.ac.uk
Hand gesture recognition • Liang, X., Ghannam, R., & Heidari, H. (2018). Wrist-Worn Gesture Sensing With Wearable Intelligence. IEEE Sensors Journal , 19 (3), 1082-1090.
Power Harvester Max=46.4mW Max=5.64mW Vout=3V Vbattery =4.2V
Fabricate Flexible Piezoelectric Sensor Solder Copper tape High PDMS+KNLN Coating Silver epoxy tempe conductive rature Flexible sensor High Mixing Poling voltage Flexible Vacuum Mould piezo sensor
Hand Gesture Recognition of Piezo Sensor Max Algorithm KNN BDT SVM Min Peak to peak Time domain RMS MAD Accuracy with 96.49% 92.86% 98.25% Autoregression row data Selected coefficient features Peak frequency Accuracy with 73.68% 70.18% 85.95% Median features extraction frequency Frequency Mean domain frequency Time(s) 24.53 4.25 485 Spectral moments ……
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