Abstract
A key skill in archery is the ability to suppress postural tremor while aiming at a target. Providing feedback during daily archery practice is a potentially effective way of suppressing tremor. However, postural tremor is subtle and difficult to measure using vision-based techniques. This article proposes a feedback method that uses a bow equipped with a small, lightweight acceleration sensor. First, we automatically detect an archer's shooting execution cycle, including the aiming, release, and follow-through phases, by using binary classification, and then, we quantify postural tremor during aiming. Then, from the quantified postural tremor, we regress the expected total score that the archer would obtain in a series of shots during a real game. We performed an experiment with 11 members of a university archery club and achieved 1) a precision of 0.72 and recall of 0.80 in shooting detection and 2) an absolute correlation coefficient of 0.74 in score prediction with leave-one-subject-out cross-validation.
Original language | English |
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Article number | 9321369 |
Pages (from-to) | 221-228 |
Number of pages | 8 |
Journal | IEEE Transactions on Human-Machine Systems |
Volume | 51 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2021 Jun |
Keywords
- Acceleration
- event detection
- motion analysis
- sports equipment
ASJC Scopus subject areas
- Human Factors and Ergonomics
- Control and Systems Engineering
- Signal Processing
- Human-Computer Interaction
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence