A Novel Intensity-Based Approach to Increasing Prefrontal Cerebral Oxygenation by Walking Exercise.

cardiac force meter hemoencephalography prefrontal cerebral oxygenation regional cerebral blood flow walking exercise

Journal

Journal of personalized medicine
ISSN: 2075-4426
Titre abrégé: J Pers Med
Pays: Switzerland
ID NLM: 101602269

Informations de publication

Date de publication:
22 Mar 2022
Historique:
received: 10 02 2022
revised: 17 03 2022
accepted: 17 03 2022
entrez: 23 4 2022
pubmed: 24 4 2022
medline: 24 4 2022
Statut: epublish

Résumé

Regional cerebral blood flow (rCBF) increases after moderately intense exercise and is significantly correlated with cognitive function. However, no intensity-based physiological indicator for enhancing rCBF during low- to-moderate-intensity exercise has been proposed. The purpose of this study was to develop a physiological indicator housed in a wearable device to determine whether low-to-moderate intensity walking can increase rCBF. A cross-sectional study with four parallel arms was performed. Each of 114 participants was randomly assigned to either the moderate, low-to-moderate, low, or very low walking intensity groups. A novel dynamic cardiac force meter (CFM) was used to quantify walking intensity. Heart rate and hemoencephalography (HEG) were measured during each phase of the session. Compared to baseline, HEG significantly increased in both the submaximal exercise and recovery phases in members of the low-to-moderate intensity group but not the very low intensity group. Low-to-moderate intensity walking improves prefrontal cerebral blood oxygenation. The present results demonstrate the usefulness of a dynamic CFM housed in a wearable device for quantifying the intensity of walking exercise aimed at increasing prefrontal blood oxygenation. The results of the study may help guide further development of exercise strategies for brain disease patients and the ageing population.

Identifiants

pubmed: 35455626
pii: jpm12040510
doi: 10.3390/jpm12040510
pmc: PMC9027192
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Ministry of Science and Technology, Taiwan
ID : MOST 109-3111-B-016 -020
Organisme : Ministry of Science and Technology
ID : MOST 108-2314-B-016 -030

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Auteurs

Ya-Wen Hsiao (YW)

School of Nursing, National Defense Medical Center, No 161, Sec. 6, Minquan E. Road, Neihu Dist., Taipei 11490, Taiwan.
Department of Nursing, Tri-Service General Hospital, No 325, Sec. 2, Chenggong Rd., Neihu Dist., Taipei 10490, Taiwan.

Hsin-Ya Tzeng (HY)

School of Nursing, National Defense Medical Center, No 161, Sec. 6, Minquan E. Road, Neihu Dist., Taipei 11490, Taiwan.
Department of Nursing, Tri-Service General Hospital, No 325, Sec. 2, Chenggong Rd., Neihu Dist., Taipei 10490, Taiwan.

Chi-Ming Chu (CM)

Division of Biostatistics and Medical Informatics, Department of Epidemiology, School of Public Health, National Defense Medical Center, Taipei 114201, Taiwan.
Graduate Institute of Life Sciences, National Defense Medical Center, Taipei 114201, Taiwan.
Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei 114201, Taiwan.
Big Data Research Center, Fu-Jen Catholic University, New Taipei City 242062, Taiwan.
Department of Public Health, School of Public Health, China Medical University, Taichung 404328, Taiwan.
Department of Public Health, Kaohsiung Medical University, Kaohsiung 807378, Taiwan.

Hsiang-Yun Lan (HY)

School of Nursing, National Defense Medical Center, No 161, Sec. 6, Minquan E. Road, Neihu Dist., Taipei 11490, Taiwan.

Hui-Hsun Chiang (HH)

School of Nursing, National Defense Medical Center, No 161, Sec. 6, Minquan E. Road, Neihu Dist., Taipei 11490, Taiwan.

Classifications MeSH