当社グループは 3,000 以上の世界的なカンファレンスシリーズ 米国、ヨーロッパ、世界中で毎年イベントが開催されます。 1,000 のより科学的な学会からの支援を受けたアジア および 700 以上の オープン アクセスを発行ジャーナルには 50,000 人以上の著名人が掲載されており、科学者が編集委員として名高い
。オープンアクセスジャーナルはより多くの読者と引用を獲得
700 ジャーナル と 15,000,000 人の読者 各ジャーナルは 25,000 人以上の読者を獲得
Paige Dudley, David R Bassett, Dinesh John and Scott E Crouter
Purpose: To examine the validity of an armband physical activity monitor in estimating energy expenditure (EE) over a wide range of physical activities. Methods: 68 participants (mean age=39.5 ± 13.0 yrs) performed one of three routines consisting of six activities (approximately 10 min each) while wearing the armband and the Cosmed K4b2 portable metabolic unit. Routine 1 (n=25) involved indoor home-based activities, routine 2 (n=22) involved miscellaneous activities, and routine 3 (n=21) involved outdoor aerobic activities. Results: Mean differences between the EE values in METs (criterion minus estimated) are as follows. Routine 1: watching TV (-0.1), reading (-0.1), laundry (0.1), ironing (-1.3), light cleaning (-0.4), and aerobics (0.4). Routine 2: driving (-0.6), Frisbee golf (-0.9), grass trimming (-0.5), gardening (-1.5), moving dirt with a wheelbarrow (-0.1), loading and unloading boxes (0.1); Routine 3: sidewalk walking (-1.0), track walking (-0.8), walking with a bag (-0.6), tennis (1.6), track running (2.2), and road running (2.1). The armband significantly overestimated EE during several light-to-moderate intensity activities such as driving (by 74%), ironing (by 70%), gardening (by 55%), light cleaning (by 15%), Frisbee golf (by 24%), and sidewalk walking (by 26%) (P<0.05). The arm band significantly underestimated high intensity activities including tennis (by 20%), and track or road running (by 20%). Conclusion: Although the armband provided mean EE estimates within 16% of the criterion for nine of the 18 activities, predictions for several activities were significantly different from the criterion. The armband prediction algorithms could be refined to increase the accuracy of EE estimations.