For total EE , correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices .
For active EE , correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices .
The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome .
Triaxial and multisensor devices tend to be more valid monitors .
The assessment of physical activity in healthy population s and in those with chronic diseases is challenging .
The aim of this systematic review was to identify whether available activity monitors ( AM ) have been appropriately vali date d for use in assessing physical activity in these groups .
Comparison of two different physical activity monitors
Background Underst and ing the relationships between  physical activity ( PA ) and disease has become a major area of research interest . Activity monitors , devices that quantify free-living PA for prolonged periods of time ( days or weeks ) , are increasingly being used to estimate PA . A range of different activity monitors br and s are available for investigators to use , but little is known about how they respond to different levels of PA in the field , nor if data conversion between br and s is possible . Methods 56 women and men were fitted with two different activity monitors , the Actigraph ™ ( Actigraph LLC ; AGR ) and the Actical ™ ( Mini-Mitter Co. ; MM ) for 15 days . Both activity monitors were fixed to an elasticized belt worn over the hip , with the anterior and posterior position of the activity monitors r and omized . Differences between activity monitors and the validity of br and inter-conversion were measured by t-tests , Pearson correlations , Bl and -Altman plots , and coefficients of variation ( CV ) . Results The AGR detected a significantly greater amount of daily PA ( 216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min , P < 0.0001 ) . The average difference between activity monitors expressed as a CV were 3.1 and 15.5 % for log-transformed and raw data , respectively . When a conversion equation was applied to convert data sets from one br and to another , the differences were no longer significant , with CV 's of 2.2 and 11.7 % , log-transformed and raw data , respectively . Conclusion Although activity monitors predict PA on the same scale ( counts/min ) , the results between these two br and s are not directly comparable . However , the data are comparable if a conversion equation is applied , with better results for log-transformed data
For total EE , correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices .
For active EE , correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices .
The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome .
Triaxial and multisensor devices tend to be more valid monitors .
The assessment of physical activity in healthy population s and in those with chronic diseases is challenging .
The aim of this systematic review was to identify whether available activity monitors ( AM ) have been appropriately vali date d for use in assessing physical activity in these groups .