Feature extraction of performance variables in elite half-pipe snowboarding using body mounted inertial sensors

Abstract

Recent analysis of elite-level half-pipe snowboard competition has revealed a number of sport specific key performance variables (KPV's) that correlate well to score 1 . Information on these variables is difficult to acquire and analyse, relying on collection and labour intensive manual post processing of video data. This paper presents the use of inertial sensors as a user-friendly alternative and subsequently implements signal processing routines to ultimately provide automated, sport specific feedback to coaches and athletes. The author has recently shown that the key performance variables (KPV's) of total air-time (TAT) and average degree of rotation (ADR) achieved during elite half-pipe snowboarding competition show strong correlation with an athlete's subjectively judged score 1 . Utilising Micro-Electrochemical System (MEMS) sensors (tri-axial accelerometers) this paper demonstrates that air-time (AT) achieved during half-pipe snowboarding can be detected and calculated accurately using basic signal processing techniques. Characterisation of the variations in aerial acrobatic manoeuvres and the associated calculation of exact degree of rotation (DR) achieved is a likely extension of this research. The technique developed used a two-pass method to detect locations of half-pipe snowboard runs using power density in the frequency domain and subsequently utilises a threshold based search algorithm in the time domain to calculate air-times associated with individual aerial acrobatic manoeuvres. This technique correctly identified the air-times of 100 percent of aerial acrobatic manoeuvres within each half-pipe snowboarding run (n = 92 aerial acrobatic manoeuvres from 4 subjects) and displayed a very strong 12 correlation with a video based reference standard for air-time calculation (r = 0.78 ± 0.08; p value < 0.0001; SEE = 0.08 ×/÷ 1.16; mean bias = -0.03 ± 0.02s) (value ± or ×/÷ 95% CL).

The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices

“…In the gym, sensor data from balance board training [14,15] has been used to provide feedback on the performance quality. Furthermore, body-worn inertial sensors have been used for the assessment of (professional) athletes in sports such as snow-boarding [16], swimming [17] and running [18]. Beyond applications in sports, similar systems have been employed to assess professional skills, e.g.…”

Inertial sensor for objective evaluation of swimmer performance

“…Recently the use of MEMS technology based miniature inertial sensors, accelerometers and gyroscopes, has got a lot of interest in sports applications [2,3]. Mainly this has happened because these sensors are independent from other signal sources (they are passive in that respect).…”

Automated scoring for elite half‐pipe snowboard competition: Important sporting development or techno distraction?

“…We have previously shown that air time can be objectively calculated using video-based analysis and that there is a significant and large linear relationship (r 5 0.5670.26, Po0.001, r 2 5 0.31, Standard error of the estimate (SEE) 5 4.60, n 5 30) between total air time and an athletes subjectively-judged score during two FIS World Cup half-pipe snowboarding competition finals held in Bardonecchia, Italy in 2005 [3]. The two-pass signal-processing technique promoted within this study was able to detect 100 per cent of the aerial acrobatic maneuvers performed [3]. This is a result of the labor-intensive nature of the manual post-processing of video data and the subsequent time delay in information feedback.…”

“…The components of air time and amplitude, however, are currently assessed subjectively by elite-level coaches and competition judges when providing performance feedback to athletes. We therefore promoted the use of microtechnology to provide automated objective feedback on air time and recently showed that air time can be accurately and reliably calculated using inertial sensor output (provided by tri-axial accelerometers) and basic signal-processing techniques [3]. It is believed, however, that the use of video analysis to objectively calculate information on air time during halfpipe snowboarding would be difficult to incorporate on a routine basis.…”