A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Segmentation boundaries in accelerometer data of arm motion induced by music : online computation and perceptual assessment (2022)
Mendoza Garay, J. I. (2022). Segmentation boundaries in accelerometer data of arm motion induced by music : online computation and perceptual assessment. Human Technology, 18(3), 250-266. https://doi.org/10.14254/1795-6889.2022.18-3.4
JYU-tekijät tai -toimittajat
Julkaisun tiedot
Julkaisun kaikki tekijät tai toimittajat: Mendoza Garay, Juan Ignacio
Lehti tai sarja: Human Technology
eISSN: 1795-6889
Julkaisuvuosi: 2022
Ilmestymispäivä: 28.12.2022
Volyymi: 18
Lehden numero: 3
Artikkelin sivunumerot: 250-266
Kustantaja: Centre of Sociological Research
Julkaisumaa: Puola
Julkaisun kieli: englanti
DOI: https://doi.org/10.14254/1795-6889.2022.18-3.4
Julkaisun avoin saatavuus: Avoimesti saatavilla
Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava
Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/84786
Lisätietoja: Articles
Tiivistelmä
Segmentation is a cognitive process involved in the understanding of information perceived through the senses. Likewise, the automatic segmentation of data captured by sensors may be used for the identification of patterns. This study is concerned with the segmentation of dancing motion captured by accelerometry and its possible applications, such as pattern learning and recognition, or gestural control of devices. To that effect, an automatic segmentation system was formulated and tested. Two participants were asked to ‘dance with one arm’ while their motion was measured by an accelerometer. The performances were recorded on video, and manually segmented by six annotators later. The annotations were used to optimize the automatic segmentation system, maximizing a novel similarity score between computed and annotated segmentations. The computed segmentations with highest similarity to each annotation were then manually assessed by the annotators, resulting in Precision between 0.71 and 0.89, and Recall between 0.82 to 1.
YSO-asiasanat: tanssi; liike; kiihtyvyys; mittaus; liikeanalyysi; kognitiiviset prosessit; havainnointi; segmentointi
Vapaat asiasanat: gestural interface; perceptual evaluation; temporal segmentation; accelerometer; bodily motion; similarity
Liittyvät organisaatiot
OKM-raportointi: Kyllä
Raportointivuosi: 2022
JUFO-taso: 1