Physiological responses to physical activity: A multi-sensor wearable study across activity intensity, age, gender, body weight, and BMI variability

身体活动引起的生理反应:一项涵盖活动强度、年龄、性别、体重和BMI变异性的多传感器可穿戴设备研究

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Abstract

Designing exercise interventions and assessing cardiovascular health depend on an understanding of how physiological parameters react to physical activity. Twenty-two healthy adults (ages 20-53, both sexes, varying fitness levels) participated in this study to examine the effects of 3 activity levels on heart rate (HR), systolic blood pressure (SBP) and diastolic blood pressure, and arterial oxygen saturation (peripheral oxygen saturation). The activities levels were sitting (rest), walking (~3 metabolic equivalents of tasks), and running (~7 metabolic equivalents of tasks), and each lasted roughly 5 minutes. For ongoing physiological monitoring, participants wore a specially designed multi-sensor device that combined force, photoplethysmography, inertial measurement unit, and electrocardiogram sensors. The physiological signals utilized in this investigation were supplemented by internal sensor validation and sourced from open-source datasets made available through PhysioNet. Higher activity intensity was associated with significant increases in HR (P < .001) and SBP (P < .01), according to repeated measures analysis of variance. HR increased stepwise across all activity conditions, while SBP significantly rose from sitting to running. Peripheral oxygen saturation values showed a slight postexercise decline, among older participants (P = .03), but they stayed within normal ranges (>95%). Age and weight were found to have moderate relationships with cardiovascular responses, specifically SBP, according to regression analysis. The random forest model's low predictive accuracy (R2 = 0.057) when predicting HR from physiological and demographic inputs emphasized the necessity for additional behavioral or contextual data. These results demonstrate the impact of age gender weight and body mass index on cardiovascular dynamics while showcasing how multi-sensor wearables detect individual physiological responses. This work's implications support customized exercise recommendations along with hypertension risk assessment and endurance training approaches for both clinical and athletic populations.

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