File(s) under permanent embargo
Machine Learning Aided Minimal Sensor based Hand Gesture Character Recognition
conference contribution
posted on 2023-03-10, 05:34 authored by N Zaidi, P Kumari, Sutharshan RajasegararSutharshan Rajasegarar, Chandan KarmakarChandan KarmakarHand gesture recognition is the process of detecting the hand movements via sensor measurements for detecting an activity, such as writing a letter or a number. Recognising the handwritten characters using wearable devices enables machine-human interaction to occur without the need for a communication method. An intelligent automated framework is required to accurately detect the handwritten characters using wrist worn sensor signals, in particular, with minimal number of sensors. Moreover, the system developed needs to have the capacity to recognise the characters written in different sizes. In order to address these, we analyse performance of several machine learning models using single/multiple sensors namely, accelerometer or/and gyroscope, for recognising hand gesture characters including alphabet and numbers of varying sizes. We formulate a set of features that enable robust and accurate detection of the characters.We performed novel data collection using an off-the-shelf wrist-worn sensor based device, and evaluated our framework to detect the different characters effectively. The maximum accuracy (90.40%) was achieved using both sensors and Random Forest (RF) model. This was dropped to 82.51% for the same model using accelerometer sensor alone. Using the gyroscope sensor, an overall average accuracy of 80.16% was achieved with the Forward Neural Network (FNN) model. Although the model based on both sensors showed the best performance, our evaluation reveals that it is feasible to develop a machine learning model using single sensor to detect hand gesture characters of varying sizes with reasonable (≥ 80%) accuracy.
History
Volume
00Location
Shenzhen, ChinaPublisher DOI
Start date
2022-10-13End date
2022-10-16ISBN-13
9781665473309Language
EnglishPublication classification
E1 Full written paper - refereedTitle of proceedings
DSAA 2022 : Proceedings of the IEEE 9th International Conference on Data Science and Advanced Analytics 2022Event
IEEE International Conference on Data Science and Advanced Analytics (9th : 2022 : Shenzhen, China)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
Categories
No categories selectedLicence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC