Health-Related Physical Fitness Level From Smartwatches
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 80
- 试验地点
- 1
- 主要终点
- Maximum Oxygen Consumption (VO2max)
研究概览
简要总结
Health-related physical fitness (HRPF) has demonstrated high clinical relevance, and its level is associated with the ability to perform activities of daily living with vigor and a lower risk of chronic disease. Consequently, exercise prescription guidelines recommend improving HRPF as a focus for prevention and rehabilitation programs. Measuring and tracking HRPF often requires specialized equipment and personnel, which are expensive and less applicable to the general population. Wearables may mitigate this issue by providing useful estimates of the HRPF.
详细描述
Health-related physical fitness (HRPF) has high clinical relevance [1]. It is associated with the ability to perform activities of daily living with vigor and a lower risk of chronic disease [2]. Consequently, exercise prescription guidelines recommend improving HRPF as a focus for prevention and rehabilitation programs [3]. The American College of Sports Medicine (ACSM) [3] grouped the HRFP into five domains: cardiorespiratory endurance, body composition, muscular strength, muscular endurance, and flexibility. However, measuring and tracking the fitness levels for all HRPF domains requires specialized laboratory equipment and personnel, which are expensive and less applicable to the general population. Wearable technology mitigates this issue and has proven to be a reliable alternative capable of providing useful estimates of the HRPF [4] [5] [6, 7]. Previous work has predicted ACSM HRPF domains from anthropometric and laboratory bioelectrical impedance analysis data (BIA) [8] [9]. Nevertheless, their data are based on the National Fitness Award (NFA), a nationwide test used to assess the physical fitness of the general South Korean population that is collected using specialized laboratory equipment under the supervision of health professionals.
Current advances in wearables may allow us to estimate the fitness level for all HRPF domains using only smartwatch data, enabling economic, non-intrusive predictions and being available during the user's daily routine. The complete characterization of health-related fitness as a multidimensional depiction of the user's fitness status can be used to track health status continuously and to design specialized training prescriptions. The main goal of this study is to estimate the fitness level for all HRFP domains from data obtained from smartwatches during unsupervised activities of daily living. We hypothesized that data from smartwatches could be used to estimate the fitness levels from all HRPF domains.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 20 Years 至 60 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Group 1 (Aerobically Trained)
- •20-60 years old
- •actively training or competing over the past 2 years
- •3 or more days of vigorous activity accumulating approximately least 1500 MET min/week or 7 days of any combination of walking, moderate, or vigorous intense activities achieving a minimum of 3000 MET min/week
- •Group 2 (Strength trained)
- •20-60 years old
- •actively training or competing over the past 2 years
- •3 or more days of muscle-strengthening exercise at an intensity of approximately 5 out of 10
- •Group 3 (Not actively training)
- •20-60 years old
- •actively training or competing over the past 2 years
- •3 or more days of muscle-strengthening exercise at an intensity of approximately 5 out of 10
- •Group 5 (High flexibility)
- •20-60 years old
- •Sit-and-reach performance is categorized as "very good" or excellent based on the American College of Sports Medicine's sit-and-reach evaluation criteria (Table 4.16 of ACSM's Guidelines for Exercise Testing and Prescription 9th edition).
排除标准
- •Exclusion criteria are the same for all groups.
- •History of cardiovascular disease (Cardiac, peripheral vascular, or cerebrovascular disease)
- •History of stable or unstable angina
- •History of cardiac dysrhythmias causing symptoms or hemodynamic consequences
- •History of hypertrophic cardiomyopathy
- •History of cardiac valvular disease (e.g., aortic stenosis)
- •History of pulmonary disease (Chronic obstructive pulmonary disease, asthma, interstitial lung disease, or cystic fibrosis)
- •History of pulmonary embolus
- •History of suspected or known aneurysm
- •History of metabolic disease (Diabetes mellitus (type I or II), thyroid disorders, renal or liver disease
- •History of renal disease
- •History of neuromotor, musculoskeletal, or rheumatoid disorders that are exacerbated by exercise
- •Current acute systemic infection, accompanied by fever and body aches.
- •Pain or discomfort in the chest, neck, jaw, arms, or other areas that may be due to myocardial ischemia (lack of adequate circulation)
- •Shortness of breath at rest, during daily activities, or with mild exertion
- •Dizziness or syncope (fainting)
- •Orthopnea (breathing discomfort when not in an upright position) or paroxysmal nocturnal dyspnea (interrupted breathing at night)
- •Ankle edema (swelling)
- •Palpitations (abnormal rapid beating of the heart) or tachycardia (rapid heartbeat)
- •Intermittent claudication (cramping pain and weakness in legs, especially calves, during walking due to inadequate blood supply to muscles)
- •Known heart murmur (atypical heart sound indicating a structural or functional abnormality)
- •Unusual or unexplained fatigue
- •Severe arterial hypertension (i.e., systolic blood pressure of >200 mm Hg and/or a diastolic blood pressure of >110 mm Hg) at rest.
结局指标
主要结局
Maximum Oxygen Consumption (VO2max)
时间窗: Performed 14-day after wearing the smartwatch
Maximum oxygen consumption (VO2max) will be measured using a standard Ramp protocol on a standardized treadmill.
次要结局
- % fat free mass(Performed at baseline and 14-days after wearing the smartwatch)
- Sit-and-reach distance(Performed at baseline and 14-days after wearing the smartwatch)
- # of Push-up completed(Performed at baseline and 14-days after wearing the smartwatch)
研究者
Carl Ade, M.S., Ph.D.
Associate Professor
Kansas State University