A Comparison of Head Movement Classification Methods.
Sensors (Basel)
; 24(4)2024 Feb 16.
Article
em En
| MEDLINE
| ID: mdl-38400418
ABSTRACT
To understand human behavior, it is essential to study it in the context of natural movement in immersive, three-dimensional environments. Virtual reality (VR), with head-mounted displays, offers an unprecedented compromise between ecological validity and experimental control. However, such technological advancements mean that new data streams will become more widely available, and therefore, a need arises to standardize methodologies by which these streams are analyzed. One such data stream is that of head position and rotation tracking, now made easily available from head-mounted systems. The current study presents five candidate algorithms of varying complexity for classifying head movements. Each algorithm is compared against human rater classifications and graded based on the overall agreement as well as biases in metrics such as movement onset/offset time and movement amplitude. Finally, we conclude this article by offering recommendations for the best practices and considerations for VR researchers looking to incorporate head movement analysis in their future studies.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Realidade Virtual
/
Óculos Inteligentes
Limite:
Humans
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos