A quality prediction method for weight lifting activity

• Published in: Michael Faraday IET International Summit 2015 p. 95
• Main Authors: Chatterjee, S, Chakraborty, R, Dey, N, Hore, S
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2015; The Institution of Engineering & Technology
• Subjects: Activity recognition; Bayesian analysis; Errors; Feature recognition; Hoisting; Humanities computing; Mathematical models; Neural computing techniques; Other topics in statistics; Training; sports activity recognition; false positive rate; TP rate; weight lifting activity; sports athlete; FP rate; F-Measure; quality prediction method; random forest; performance measures; relative absolute error; perfect execution; root mean squared error; multilayer perceptrons; mean absolute error; pattern classification; multilayer feedforward network; HNB classifiers; true positive rate; machine based feedback; kappa statistic; RMSE; MAE; RBFNN; health condition; hidden Naive Bayes; RAE; Bayes methods; sport; MLP-FFN; immense interest

Activity recognition has found immense interest in the field of sports activity recognition in recent time. The application has found extensive utility in giving machine based feedback on how well the performance in training is by any sports athlete. The present work proposes a model to predict the...