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Real-time arm movement recognition using FPGA

Real-time arm movement recognition using FPGA
Real-time arm movement recognition using FPGA
In this paper we present a FPGA-based system to detect three elementary arm movements in real-time (reach and retrieve, lift cup to mouth, rotation of the arm) using data from a wrist-worn accelerometer. Recognition is carried out by accurately mapping transitions of predefined, standard orientations of an accelerometer to the corresponding arm movements. The algorithm is coded in HDL and synthesized on the Altera DE2-115 FPGA board. For real-time operation, interfacing between the streaming sensor unit, host PC and the FPGA was achieved through a combination of Bluetooth, RS232 and an application software developed in C# using the .NET framework to facilitate serial port controls. The synthesized design used 1804 logic elements and recognised the performed arm movement in 41.2 μs, @50 MHz clock on the FPGA. Our experimental results show that the system can recognise all three arm movements with accuracies ranging 85%-96% for healthy subjects and 63%-75% for stroke survivors involved in 'making-a-cup-of-tea', typical of an activity of daily living (ADL).
766-769
Biswas, Dwaipayan
76983b74-d729-4aae-94c3-94d05e9b2ed4
Ajiwibawa, Gerry Juans
1d1b5c73-7b16-4e1d-8058-d2408a0ee88b
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Cranny, Andy
b82c60af-bcc5-4dd1-959b-9fd51397790e
Achner, Josy
1eb12fc1-6d4e-41e6-8e2e-6b7f4fec7daf
Klemke, Jasmin
0c095460-4faf-4d56-bfcc-c04a26e70249
Jöbges, Michael
c249b79d-ca43-46ce-86cb-a97b33a0c3d8
Biswas, Dwaipayan
76983b74-d729-4aae-94c3-94d05e9b2ed4
Ajiwibawa, Gerry Juans
1d1b5c73-7b16-4e1d-8058-d2408a0ee88b
Maharatna, Koushik
93bef0a2-e011-4622-8c56-5447da4cd5dd
Cranny, Andy
b82c60af-bcc5-4dd1-959b-9fd51397790e
Achner, Josy
1eb12fc1-6d4e-41e6-8e2e-6b7f4fec7daf
Klemke, Jasmin
0c095460-4faf-4d56-bfcc-c04a26e70249
Jöbges, Michael
c249b79d-ca43-46ce-86cb-a97b33a0c3d8

Biswas, Dwaipayan, Ajiwibawa, Gerry Juans, Maharatna, Koushik, Cranny, Andy, Achner, Josy, Klemke, Jasmin and Jöbges, Michael (2015) Real-time arm movement recognition using FPGA. IEEE International Symposium on Circuits and Systems (ISCAS), Lisbon, Portugal. 24 - 27 May 2015. pp. 766-769 . (doi:10.1109/ISCAS.2015.7168746).

Record type: Conference or Workshop Item (Poster)

Abstract

In this paper we present a FPGA-based system to detect three elementary arm movements in real-time (reach and retrieve, lift cup to mouth, rotation of the arm) using data from a wrist-worn accelerometer. Recognition is carried out by accurately mapping transitions of predefined, standard orientations of an accelerometer to the corresponding arm movements. The algorithm is coded in HDL and synthesized on the Altera DE2-115 FPGA board. For real-time operation, interfacing between the streaming sensor unit, host PC and the FPGA was achieved through a combination of Bluetooth, RS232 and an application software developed in C# using the .NET framework to facilitate serial port controls. The synthesized design used 1804 logic elements and recognised the performed arm movement in 41.2 μs, @50 MHz clock on the FPGA. Our experimental results show that the system can recognise all three arm movements with accuracies ranging 85%-96% for healthy subjects and 63%-75% for stroke survivors involved in 'making-a-cup-of-tea', typical of an activity of daily living (ADL).

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ISCAS Biswas_revised.doc - Accepted Manuscript
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Published date: 24 May 2015
Venue - Dates: IEEE International Symposium on Circuits and Systems (ISCAS), Lisbon, Portugal, 2015-05-24 - 2015-05-27
Organisations: Electronic & Software Systems

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Local EPrints ID: 384822
URI: http://eprints.soton.ac.uk/id/eprint/384822
PURE UUID: 856df135-0d02-42b5-a2d6-4bf093ac16be

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Date deposited: 13 Jan 2016 14:07
Last modified: 14 Mar 2024 22:05

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Contributors

Author: Dwaipayan Biswas
Author: Gerry Juans Ajiwibawa
Author: Koushik Maharatna
Author: Andy Cranny
Author: Josy Achner
Author: Jasmin Klemke
Author: Michael Jöbges

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