Archery Skill Assessment Using an Acceleration Sensor

Takayuki Ogasawara, Hanako Fukamachi, Kenryu Aoyagi, Shiro Kumano, Hiroyoshi Togo, Koichiro Oka

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Article number9321369
Pages (from-to)221-228
Number of pages8
JournalIEEE Transactions on Human-Machine Systems
Volume51
Issue number3
DOIs
Publication statusPublished - 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

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