Javascript must be enabled for the correct page display

Performance assessment and feedback of fitness exercises using smartphone sensors

Hooff, N.L.M van (2013) Performance assessment and feedback of fitness exercises using smartphone sensors. Master's Thesis / Essay, Human-Machine Communication.

AI-MHMC-2013-N.L.M.VAN.HOOFF.pdf - Published Version

Download (6MB) | Preview
[img] Text
AkkoordWiering.pdf - Other
Restricted to Repository staff only

Download (39kB)


Where GPS-based apps are popular for tracking outdoor fitness activities, no automated solutions exist for strength training. We use an off-the-shelf Android smartphone to provide users with feedback on tempo, movement range, and number of repetitions. Accelerometer signals are averaged into an exercise profile during calibration, after which new data can be compared with the created profile. Because exercise profiles are created by the user, our solution is suitable for many free-weight exercises. We use dynamically set thresholds to recognize repetitions. This approach is computationally efficient, and information on tempo and movement extent is retained. Feedback is given through auditory, visual and haptic modalities. Results indicate that repetition counting performance is on-par with earlier research, where performance on exercises with a rotational movement (98% correct) is higher than on exercises with a linear movement (91% correct). Trainers graded participants who received feedback sig- nificantly higher than those who did not. When directly measuring tempo and movement extent, however, the effect of the given advice on participant performance was not significant. We conclude that our app may help people perform their exercises better and more safely, but that tempo and movement range are insufficient predictors for a correctly performed exercise.

Item Type: Thesis (Master's Thesis / Essay)
Supervisor name: Wiering, xx
Degree programme: Human-Machine Communication
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 07:53
Last Modified: 02 May 2019 11:57

Actions (login required)

View Item View Item