Estimation of Energy Expenditure and Physical Activity Classification with Wearables

Estimation of Energy Expenditure and Physical Activity Classification with Wearables - EEPAC

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

NL-OMON

Registry ID

NL-OMON53398

Enrollment

Registered

2022-04-19

Start date

2022-05-18

Completion date

Unknown

Last updated

2024-04-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

algemen fysieke gezonheid energy expenditure general fitness

Interventions

None listed

Eligibility

Age

18 Years to 64 Years

Inclusion criteria

Inclusion criteria: - Aged between 18 and 64 years - Provided written informed consent - Able to be physically active assed with PAR-Q+

Exclusion criteria

Exclusion criteria: - A contraindication to physical activity - A contraindication to wearing wearables, fixed by a hypoallergenic plaster - Chronic disease - A pace maker or any chest-implanted device

Design outcomes

Primary

Measure	Time frame
The main study parameter is energy expenditure and physical activity. The main endpoint of this study is an energy expenditure estimation and physical activity classification algorithm based on wearable sensors. Energy expenditure will be measured in units of kcal per time. Physical activity will be classified as time spent in sedentary, standing, low physical activity (LPA), moderate physical activity (MPA), vigorous physical activity (VPA).	—

Measure

Time frame

The main study parameter is energy expenditure and physical activity. The main endpoint of this study is an energy expenditure estimation and physical activity classification algorithm based on wearable sensors. Energy expenditure will be measured in units of kcal per time. Physical activity will be classified as time spent in sedentary, standing, low physical activity (LPA), moderate physical activity (MPA), vigorous physical activity (VPA).

—

Secondary

Measure	Time frame
Secondary study parameters are: - Heart rate (variability) - Breathing rate - Average skin temperature - PA intensity - Body composition The secondary endpoints are: - a heart rate (variability) algorithm based on raw ECG signals - explained contribution of different bio-signals to the estimation of EE - an algorithm for the estimation of instantaneous EE	—

Countries

Netherlands

Outcome results