Detection of body postures and movements

Erasmus MC University Medical Center Rotterdam Dept. of Rehabilitation Medicine August 2013

 

Rationale: Inactivity is a well-known risk factor for the development of secondary health conditions (SHCs) in the general population as well as in people with chronic disorders. Physical activity (PA) can counteract these problems and may lead to potential health benefits. To support interventions aimed at PA or lifestyle change, it is useful to measure people’s physical behaviour objectively. Recently, the Activ8 system has been developed for this purpose. A basic characteristic of this system is the automatic detection of a set of body postures and movements (P&M).
Objective: How valid can body postures and movements be determined by the Activ8 system?
Study design: An observational validation study
Study population: 12 healthy adults
Methods: To test the validity of the Activ8 system participants performed a series of consecutive activities according to a standard protocol. Two Activ8 systems were used: one in the trouser) pocket (the prescribed location), the other attached at the front of the thigh. During the testing procedure the activities of the participants were videotaped, and analysed thereafter (reference method). P&M categories that were analyzed were sitting, standing, walking, cycling, and running.
Main study parameters/endpoints: The following primary outcomes were calculated: overall agreement, and sensitivity and predictive value for the 5 P&M categories. Additionally, duration (number of samples) of these categories were compared.
Results: The agreement between Activ8 output (pocket) and video analysis was 90.1% (inter-subject range: 67.0 to 96.6%). Sensitivity scores of P&M categories ranged from 81 to 98%, predictive value scores from 85-98%.
Conclusion: The Activ8 system appears to be a valid instrument to quantify body postures and motions. Some critical issues – such as the influence of type of pocket and pocket position- are discussed and some potential improvements are suggested.

Read the full study (pdf)…

 

Accuracy of energy expenditure in daily activities, compared to the Actigraph GTX3 +, heart rate measurement and indirect calorimetry

Objective information about sedentary behaviour and physical activity can make contributions to health. Researchers get insight into the dose-response relationship between physical activity and health and an individual gets information about his own physical activity for selfmonitoring and goal setting. The Activ8, a triaxial accelerometer, that can be carried in a subject’s trouser pocket, recognizes postures and types of physical activity (lying, sitting, standing, walking, running and cycling) Based on the registered time, in a posture or activity, and the measured accelerations (m/s2) the energy expenditure is estimated.

 

Method & results study

19 adults performed three walking activities at 2 km/h, 4 km/h and 6 km/h, three running activities at 8 km/h, 11km/h and 14 km/h on a treadmill and three cycling activities at 50 watt (40rpm), 125 watt (60rpm) and 200 watt (80rpm) on a stationary bike2 . Physical activity energy expenditure (PAEE) was estimated by heart rate, Activ8 and Actigraph in kJ/kg/min.

Estimation of energy expenditure in kJ/kg/min by heart rate, Activ8 and Actigraph for different exercise activities.

Physical activity energy expenditure (PAEE) was estimated by indirect calorimetry (Cortex) and the Activ8 in kJ/kg/min.

Discussion and conclusion

With regard tot walking and running the instruments show high correlations, although both accelerometers estimate energy expenditure using different methods. The Activ8 seems tot recognize and measure cycling activities more accurate than the Actigraph. These differences may be related to the (recommended) placement of the Actigraph on the hip, and activity recognition capacity of the Activ8.

The results from study 2 reveal that the estimated energy expenditure by the Activ8 is largely in line with indirect calorimetry. At higher running speeds an adjustment in the Activ8 algorithm might improve the estimation of energy expenditure. The workrate (energy expenditure) of cycling is determined by force x acceleration (RPM). Acceleration can be low but with a great force (cycling uphill). The Activ8 only registers acceleration and no force. Therefore the development of a validation protocol in real-life conditions is needed to have accurate estimations of energy expenditure.

Relevance

The Activ8 is an affordable activity monitor which is easy to use and seems to make acceptable estimations of energy expenditure. This makes it a promising device for both large scale research purposes and the consumer market. The Activ8 also has two additional features; it recognizes different postures and types of physical activity (lying, sitting, standing, walking, running and cycling) and is supported by an online coaching module that allows the use of the Activ8 as a means for interventions. Future research will have to demonstrate the accuracy of the Activ8 in real life validation studies and its potential as a coaching tool.

Download the poster of the Energy Expenditure validation study (pdf)..