title: A novel method for using accelerometer data to predict energy expenditure. Estimating absolute and relative physical activity intensity across age via accelerometry in adults. Comparison of two different physical activity monitors Activity-monitor accuracy in measuring step number and cadence in community-dwelling older adults. Physical activity monitor for recording energy expenditure in pregnancy Pedometer accuracy in nursing home and community-dwelling older adults. Real-time estimation of daily physical activity intensity by a triaxial accelerometer and a gravity-removal classification algorithm. Improving energy expenditure estimation by using a triaxial accelerometer. Assessment of physical activity in older individuals: a doubly labeled water study. Resistance training increases total daily energy expenditure in disabled older women with coronary heart disease. Validity of estimating minute-by-minute energy expenditure of continuous walking bouts by accelerometry Daily physical activity assessment: comparison between movement registration and doubly labeled water. Ability of different physical activity monitors to detect movement during treadmill walking. Accuracy of a novel multi-sensor board for measuring physical activity and energy expenditure Total free living energy expenditure in patients with severe chronic obstructive pulmonary disease. Validity of 10 electronic pedometers for measuring steps, distance, and energy cost. A Clinical Evaluation of a Remote Mobility Monitoring System based on SMS Messaging Step counting and energy expenditure estimation in patients with chronic obstructive pulmonary disease and healthy elderly: accuracy of 2 motion sensors. A comparison of energy expenditure estimates from the Actiheart and Actical physical activity monitors during low intensity activities, walking, and jogging Accelerometer prediction of energy expenditure: vector magnitude versus vertical axis. Physical activity-related energy expenditure with the RT3 and TriTrac accelerometers in overweight adults. Six-Minute Walk Test and Cardiopulmonary Exercise Testing in Patients With Chronic Heart Failure: A Comparative Analysis on Clinical and Prognostic Insights Calibration of the Computer Science and Applications, Inc. accelerometer. Assessment of energy expenditure in overweight women. Energy expenditure prediction using a miniaturized ear-worn sensor.
abstract: The purpose of this study was to develop a new two-regression model relating Actigraph activity counts to energy expenditure over a wide range of physical activities . Forty-eight participants [ age 35 yr ( 11.4 ) ] performed various activities chosen to represent sedentary , light , moderate , and vigorous intensities . Eighteen activities were split into three routines with each routine being performed by 20 individuals , for a total of 60 tests . Forty-five tests were r and omly selected for the development of the new equation , and 15 tests were used to cross-vali date the new equation and compare it against already existing equations . During each routine , the participant wore an Actigraph accelerometer on the hip , and oxygen consumption was simultaneously measured by a portable metabolic system . For each activity , the coefficient of variation ( CV ) for the counts per 10 s was calculated to determine whether the activity was walking/running or some other activity . If the CV was < or=10 , then a walk/run regression equation was used , whereas if the CV was > 10 , a lifestyle/leisure time physical activity regression was used . In the cross-validation group , the mean estimates using the new algorithm ( 2-regression model with an inactivity threshold ) were within 0.75 metabolic equivalents ( METs ) of measured METs for each of the activities performed ( P > or= 0.05 ) , which was a substantial improvement over the single-regression models . The new algorithm is more accurate for the prediction of energy expenditure than currently published regression equations using the Actigraph accelerometer This study examined the predictive validity of accelerometers ( ACC ) to estimate physical activity intensity ( PAI ) across age and differences in intensity predictions when expressed in relative and absolute PAI terms . Ninety adults categorized into 3 age groups ( 20 - 29 , 40 - 49 , and 60 - 69 yr ) completed a treadmill calibration study with simultaneous ACC ( 7164 Actigraph ) and oxygen-consumption assessment . Results revealed strong linear relations between ACC output and measured PAI ( R2 = .62-.89 ) across age and similar ACC cut-point ranges across age delineating absolute PAI ranges compared with previous findings . Comparing measured metabolic equivalents ( METs ) with estimated METs derived from previously published regression equations revealed that age did not affect predictive validity of ACC estimates of absolute PAI . Comparing ACC output expressed in relative vs. absolute terms across age revealed substantial differences in PAI ACC count ranges . Further work is warranted to increase the applicability ofACC use relative to PAI differences associated with physiological changes with age 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 The primary purpose of this study was to investigate the accuracy of the activPAL physical activity monitor in measuring step number and cadence in older adults .  Two pedometers ( New-Lifestyles Digi-Walker SW-200 and New-Lifestyles NL2000 ) used in clinical practice to count steps were simultaneously evaluated . Observation was the criterion measure . Twenty-one participants ( 65 - 87 yr old ) recruited from community-based exercise classes walked on a treadmill at 5 speeds ( 0.67 , 0.90 , 1.12 , 1.33 , and 1.56 m/s ) and outdoors at 3 self-selected speeds ( slow , normal , and fast ) . The absolute percentage error of the activPAL was < 1 % for all treadmill and outdoor conditions for measuring steps and cadence . With the exception of the slowest treadmill speed , the NL-2000 error was < 2 % . The SW-200 was the least accurate device , particularly at slower walking speeds . The activPAL monitor accurately recorded step number and cadence . Combined with its ability to identify primary postures , the activPAL might be a useful and versatile device for measuring activity in older adults Objective . To determine whether the energy expenditure recorded with the physical activity monitor SenseWear ™ Pro2 Armb and differs from that recorded with indirect calorimetry . Design . Cross‐sectional comparison of measures of energy expenditure . Setting . A convenient sample recruited from a r and omized controlled trial . Population . Twenty‐nine pregnant women ( 24–43years old ) . Methods . Energy expenditure was recorded with SenseWear ™ Pro2 Armb and and a portable oxygen analyzer for 90minutes while carrying out a variety of activities of different intensities . Main Outcome Measures . Energy expenditure recorded with the physical activity monitor SenseWear ™ Pro2 Armb and . Results . Comparing energy expenditure during free‐living activities , the mean differences and limits of agreements from Bl and –Altman plots was −136±343kJ , giving an underestimation of energy expenditure by 9 % . The intraclass correlation coefficient was 0.85 ( 95 % confidence interval 0.71–0.93 ; p<0.001 ) , giving 85 % of the variance explained by differences among individuals . Conclusions . SenseWear ™ Pro2 Armb and is a valid measure of energy expenditure during pregnancy PURPOSE The accuracy of pedometers has not been thoroughly tested with older adult population s. The purpose of the present study was to examine the effects of walking speed and gait disorders on the accuracy of Yamax pedometers with nursing home residents ( NH ) relative to older adults living in the community . METHODS Pedometer accuracy was evaluated against observed steps taken during a self-paced walking test ( slow , normal , and fast speeds ) in 26 NH residents and 28 seniors ' recreation center members ( SC ) . Devices were attached to clothing at the waist . Walking speed was ascertained from the timed walk and a gait assessment was conducted . Percent error was calculated as ( [ pedometer steps - observed steps]/observed steps ) x 100 . RESULTS The walking speeds of both sample s increased across self-selected paces ( P < 0.0001 ) . The community-dwelling older adults  walked significantly faster ( P < 0.0001 ) in all trials and had significantly higher ( P < 0.0001 ) gait assessment scores ( indicating fewer gait problems ) . Gait scores were positively associated with walking speed and pedometer percent error .  Pedometers significantly underestimated NH residents '  observed steps taken by 74 % ( slow ) , 55 % ( normal ) , and 46 % ( fast ) paces ( P < 0.0001 ) . In the SC sample , the instruments failed to detect 25 % , 13 % , and 7 % of actual steps taken , respectively ( P < 0.0001 ) . The magnitude of the error was greater for NH versus SC older adults ( P < 0.0001 ) across all trials . CONCLUSIONS Slow walking speed and gait disorders hamper the utility of pedometers for physical activity measurement in frail seniors , such as NH residents , when worn at the usual attachment site . Pedometers , however , can be confidently used with ostensibly healthy older adult population s for both assessment and motivation purpose We have recently developed a simple algorithm for the classification of household and locomotive activities using the ratio of unfiltered to filtered synthetic acceleration ( gravity-removal physical activity classification algorithm , GRPACA ) measured by a triaxial accelerometer . The purpose of the present study was to develop a new model for the immediate estimation of daily physical activity intensities using a triaxial accelerometer .  A total of sixty-six subjects were r and omly assigned into validation ( n 44 ) and cross-validation ( n 22 ) groups . All subjects performed fourteen activities while wearing a triaxial accelerometer in a controlled laboratory setting . During each activity , energy expenditure was measured by indirect calorimetry , and physical activity intensities were expressed as metabolic equivalents ( MET ) . The validation group displayed strong relationships between measured MET and filtered synthetic accelerations for household ( r 0·907 , P < 0·001 ) and locomotive ( r 0·961 , P < 0·001 ) activities . In the cross-validation group , two GRPACA-based linear regression models provided highly accurate MET estimation for household and locomotive activities . Results were similar when equations were developed by non-linear regression or sex-specific linear or non-linear regressions . Sedentary activities were also accurately estimated by the specific linear regression classified from other activity counts . Therefore , the use of a triaxial accelerometer in combination with a GRPACA permits more accurate and immediate estimation of daily physical activity intensities , compared with previously reported cut-off classification models . This method may be useful for field investigations as well as for self-monitoring by general users In our study of 125 subjects ( 53 men and 72 women ) for two 24-h periods , we vali date d energy expenditure ( EE ) , estimated by a triaxial accelerometer ( Tritrac-R3D ) , by using a whole-room indirect calorimeter  under close-to-normal living conditions . The estimated EE was correlated with the measured total EE for the 2 days ( r = 0 . 925 and r = 0.855 ; P < 0.001 ) and in minute-by-minute EE ( P < 0.01 ) . Resting EE formulated by the Tritrac was found to be similar to the measured values [ st and ard errors of estimation ( SEE ) = 0.112 W/kg ; P = 0.822 ] . The Tritrac significantly underestimated total EE , EE for physical activities , EE of sedentary and light-intensity activities , and EE for exercise such as stepping ( all P < 0.001 ) . We developed a linear and a nonlinear model to predict EE by using the acceleration components from the Tritrac . Predicted EE was significantly improved with both models in estimating total EE , total EE for physical activities , EE in low-intensity activities , minute-by-minute averaged relative difference , and minute-by-minute SEE ( all P < 0 . 05 ) . Furthermore , with our generalized models and by using subjects ' physical characteristics and body acceleration , EE can be estimated with higher accuracy ( averaged SEE = 0.418 W/kg ) than with the Tritrac model We compared the accuracy of two physical activity recall question naires and a motion detector in 45- to 84-yr-old women ( n = 35 ) and men ( n = 32 ) , using doubly labeled water ( DLW ) in conjunction with indirect calorimetry as the criterion measure . Subjects were administered the  Yale Physical Activity Survey ( YPAS ) and  Minnesota Leisure Time Physical Activity Question naire ( LTA ) .  Physical activity energy expenditure was determined over a 10-day period by using a Caltrac uniaxial accelerometer and DLW in conjunction with indirect calorimetry . In older women , Minnesota LTA ( 386 + /- 228 kcal/day ) and Caltrac ( 379 + /- 162 kcal/day ) underestimated physical activity by approximately 55 % compared with DLW ( 873 + /- 244 kcal/day ) . No difference was observed between daily physical activity measured by the YPAS ( 863 + /- 447 kcal/day ) and DLW in older women . In older men , Minnesota LTA ( 459 + /- 288 kcal/day ) and Caltrac ( 554 + /- 242 kcal/day ) underestimated daily physical activity by approximately 50 - 60 % compared with DLW ( 1,211 + /- 429 kcal/day ) . No difference was found between physical activity measured by the YPAS ( 1,107 + /- 612 kcal/day ) and DLW in older men . Despite no difference in mean physical activity levels between YPAS and DLW in women and men , Bl and and Altman ( Lancet 1 : 307 - 310 , 1986 ) analyses demonstrated poor concordance between DLW and YPAS ( i.e. , limits of agreement = -1,310 - 1,518 kcal/day ) . Our data suggest that the Minnesota LTA recall and Caltrac uniaxial accelerometer may significantly underestimate free-living daily physical activity energy expenditure in older women and men . Although the YPAS compares favorably with DLW on a group basis , its use as a proxy measure of individual daily physical activity energy expenditure may be limited in older women and men Physical activity energy expenditure ( PAEE ) is a determinant of prognosis and fitness in older patients with coronary heart disease ( CHD ) .  PAEE and total energy expenditure ( TEE ) are closely related to fatness , physical function , and metabolic risk in older individuals . The goal of this study was to assess effects of resistance training on PAEE , TEE , and fitness in older women with chronic CHD and physical activity limitations ( N = 51 , mean age : 72 + 5 yr ) . The study intervention consisted of a progressive , 6-mo program of resistance training vs. a control group condition of low-intensity yoga and deep breathing . The study interventions were completed by 42 of the 51 participants . The intervention group manifested a 177 + /- 213 kcal/day ( + 9 % ) increase in TEE , pre- to posttraining , measured by the doubly labeled water technique during a nonexercise 10-day period ( P < 0.03 vs. controls ) . This was due to a 50 + /- 74 kcal/day ( 4 % ) increase in resting metabolic rate measured by indirect calorimetry ( P < 0.01 , P < 0.05 vs. controls ) and a 123 + /- 214 kcal/day ( 9 % ) increase in PAEE ( P < 0.03 , P = 0.12 vs. controls ) . Resistance training was associated with significant increases in upper and lower body strength , but no change in fat-free mass , measured by dual X-ray absorptiometry , or left ventricular function , measured by echocardiography and Doppler . Women in the control group showed no alterations in TEE or its determinants . There were no changes between groups in body composition , aerobic capacity , or measures of mental depression . These results demonstrate that resistance training of 6-mo duration leads to an increase in TEE and PAEE in older women with chronic CHD Background Objective measurement of physical activity remains an important challenge . For wearable monitors such as accelerometer-based physical activity monitors , more accurate methods are needed to convert activity counts into energy expenditure ( EE ) . Purpose The purpose of this study was to examine the accuracy of the refined Crouter 2-Regression Model ( C2RM ) for estimating EE during the transition from rest to walking and walking to rest . A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined C2RM and the 2006 C2RM . Methods Thirty volunteers ( age , 28 ± 7.7 yrs ) performed 15 minutes of seated rest , 8 minutes of over-ground walking , and 8 minutes of seated rest . An ActiGraph GT1 M accelerometer and Cosmed K4b2 portable metabolic system were worn during all activities . Participants were r and omly assigned to start the walking bout at 0 , 20 , or 40 s into the minute ( according to the ActiGraph clock ) . Acceleration data were analyzed by two methods : 2006 Crouter model and a new refined model . Results The 2006 Crouter 2-Regression model over-predicted measured kcal kg-1 hr-1 during the first and last transitional minutes of the 20-s and 40-s walking conditions ( P < 0.001 ) . It also over-predicted the average EE for a walking bout ( 4.0 ± 0.5 kcal kg-1 hr-1 ) , compared to both the measured kcal kg-1 hr-1 ( 3.6 ± 0.7 kcal kg-1 hr-1 ) and the refined Crouter model ( 3.5 ± 0.5 kcal kg-1 hr-1 ) ( P < 0.05 ) . Conclusion The 2006 Crouter 2-regression model over-predicts EE at the beginning and end of walking bouts , due to high variability in accelerometer counts during the transitional minutes . The new refined model eliminates this problem and results in a more accurate prediction of EE during walking The use of movement registration for daily physical activity assessment was evaluated during a 7-day period in 30 free-living subjects . Body movement was registered with a Tracmor motion sensor consisting of a triaxial accelerometer and a data unit for on-line processing of accelerometer output over 1-min intervals . Average Tracmor output was correlated against four different energy estimates : 1 ) average daily metabolic rate ( ADMR ) , determined with doubly labeled water ; 2 ) ADMR-sleeping metabolic rate ( SMR ; determined in a respiration chamber ) ; 3 ) ( ADMR-SMR ) per kilogram of body mass ; and 4 ) the overall physical activity level ( PAL = ADMR/SMR ) . The highest correlation was found for the relationship between Tracmor output and PAL ( r = 0.58 ) . After correction for Tracmor values arising from vibrations produced by transportation means , this correlation was improved to 0.73 . There was no difference between Tracmor output and PAL in discriminating between overall activity levels with " low " ( PAL < 1.60 ) , " moderate " ( 1.60 < or = PAL < or = 1.85 ) , and " high " ( PAL > 1.85 ) intensity . It is concluded that the Tracmor can be used in free-living subjects to distinguish among interindividual as well as intraindividual levels of daily physical activity This study assessed the ability of four different activity monitors to discriminate changes in treadmill walking velocity . The relationships between walking velocity and bodily movement and between bodily movement and energy expenditure determined by indirect calorimetry ( IC-EE or METs ) were determined . Twenty-eight subjects walked at 3.2 , 4.0 , 4.8 , 5.6 , and 6.4 km/h ( 0 % grade ) for 30 min on separate occasions . The Tritrac-R3D ( TT ) , Computer Science & Applications , Inc. ( CSA ) , and Mini-Logger ( ML ) activity monitors that measure bodily acceleration in one or three planes , and a Yamax Digiwalker-500 ( YX ) that records footsteps , were secured at the waistline of each subject . CSA monitors were also worn at the wrist and ankle . Walking velocity and bodily movement were significantly related ( r = 0.89 to 0.93 ) for TT , CSA , ML , and YX . Importantly , changing each walking velocity produced significant changes in bodily movement that was detected by each monitor . Bodily movement and IC-EE were significantly related for TT , CSA , ML , and YX ( r = 0.47 to 0.94 ) . Compared to IC-EE , and at all walking speeds , EE was significantly overestimated by the TT , and EE was significantly underestimated by the YX . These results indicate that the activity monitors can differentiate bodily movement associated with walking at slow speeds better than they can estimate energy expenditure associated with walking at slow speeds The ability to relate physical activity to health depends on accurate measurement . Yet , none of the available methods are fully satisfactory due to several factors . This study examined the accuracy of a multi-sensor board ( MSB ) that infers activity types ( sitting , st and ing , walking , stair climbing , and running ) and estimates energy expenditure in 57 adults ( 32 females ) 39.2 ± 13.5 years . In the laboratory , subjects walked and ran on a treadmill over a select range of speeds and grade s for 3 min each ( six stages in r and om order ) while connected to a stationary calorimeter , preceded and followed by brief sitting and st and ing . On a different day , subjects completed scripted activities in the field connected to a portable calorimeter . The MSB was attached to a strap at the right hip . Subjects repeated one condition ( r and omly selected ) on the third day . Accuracy of inferred activities compared with recorded activities ( correctly identified activities/total activities × 100 ) was 97 and 84 % in the laboratory and field , respectively . Absolute accuracy of energy expenditure [ 100 – absolute value ( kilocalories MSB – kilocalories calorimeter/kilocalories calorimeter ) × 100 ] was 89 and 76 % in the laboratory and field , the later being different ( P < 0.05 ) from the calorimeter . Test – retest reliability for energy expenditure was significant in both setting s ( P < 0.0001 ; r = 0.97 ) . In general , the MSB provides accurate measures of activity type in laboratory and field setting s and energy expenditure during treadmill walking and running although the device underestimates energy expenditure in the field Resting  energy expenditure ( REE )  is often elevated in patients with chronic obstructive pulmonary disease ( COPD ) , but no data are available regarding total energy expenditure in free living conditions . We compared total daily energy expenditure ( TDE ) in eight COPD patients ( FEV1 36 + /- 13 % ) admitted to a pulmonary rehabilitation center and eight independently living healthy subjects , matched for sex , age , and body mass index ( BMI ) .  TDE was measured over a 2-wk interval using doubly labeled water in combination with measurement of REE and body composition .  The COPD patients had a significantly higher TDE than the healthy subjects ( 2,499 + /- 320 kcal/d and 2,107 + /- 88 kcal/d , respectively , p < 0.01 ) . The nonresting component of TDE ( TDE-REE : physical activity and diet-induced thermogenesis [ DIT ] ) was significantly higher in the COPD patients than in the healthy subjects , result ing in a ratio between TDE and REE of 1.7 + /- 0.2 and 1.4 + /- 0.1 , respectively ( p < 0.01 ) . The results indicate that COPD patients exhibit an increased TDE in comparison with healthy subjects . The difference could by attributed to an increase in the nonresting component of TDE , since REE was comparable between the groups PURPOSE This study examined the effects of walking speed on the accuracy and reliability of 10 pedometers : Yamasa Skeletone ( SK ) , Sportline 330 ( SL330 ) and 345 ( SL345 ) , Omron ( OM ) , Yamax Digiwalker SW-701 ( DW ) , Kenz Lifecorder ( KZ ) , New Lifestyles 2000 ( NL ) , Oregon Scientific ( OR ) , Freestyle Pacer Pro ( FR ) , and Walk4Life LS 2525 ( WL ) . METHODS Ten subjects ( 33 + /- 12 yr ) walked on a treadmill at various speeds ( 54 , 67 , 80 , 94 , and 107 m x min-1 ) for 5-min stages . Simultaneously , an investigator determined  steps by a h and counter and  energy expenditure  ( kcal ) by indirect calorimetry . Each br and was measured on the right and left sides . RESULTS Correlation coefficients between right and left sides exceeded 0.81 for all pedometers except OR ( 0.76 ) and SL345 ( 0.57 ) . Most pedometers underestimated steps at 54 m x min-1 , but accuracy for step counting improved at faster speeds . At 80 m x min-1 and above , six models ( SK , OM , DW , KZ , NL , and WL ) gave mean values that were within + /- 1 % of actual steps . Six pedometers displayed the distance traveled . Most of them estimated mean distance to within + /- 10 % at 80 m x min-1 but overestimated distance at slower speeds and underestimated distance at faster speeds . Eight pedometers displayed kilocalories , but except for KZ and NL , it is unclear whether this should reflect net or gross kilocalories . If one assumes they display net kilocalories , the general trend was an overestimation of kilocalories at every speed . If one assumes they display gross kilocalorie , then seven of the eight pedometers were accurate to within + /-30 % at all speeds . CONCLUSION In general , pedometers are most accurate for assessing steps , less accurate for assessing distance , and even less accurate for assessing kilocalories The objective of this work was to evaluate the accuracy and viability of a  mobility telemonitoring system  , based on the short message service ( SMS ) , to monitor the functional mobility of elderly subjects in an unsupervised environment A clinical trial was conducted consisting of 6 elderly subjects ; 3 male , 3 female ( mean : 81.7 , SD : 5.09 ) .  Mobility was monitored using an accelerometer based portable unit worn by each monitored subject for eleven hours . Every 15 minutes the mobility of the subject was summarized and transmitted as an SMS message from the portable unit to a remote server for long term analysis . The activPALtrade Trio Professional physical activity logger  was simultaneously used for comparison with the portable unit . On conclusion of the trial each subject completed a question naire detailing their satisfaction with the portable unit and any recommendations for improvements . Overall a percentage difference of 2.31 % was found between the activPALtrade Trio and the portable unit for the detection of sitting . For the combined postures of st and ing and walking the percentage difference was calculated as 2.9 % . A bivariate correlation and regression analysis was performed on the entire data set of one subject . Strong positive correlation 's were found for the detection of sitting ( r = 0.996 ) and for the combined postures of st and ing and walking ( r = 0.994 ) . Subjects suggested that a lighter , smaller and wireless unit would be more effective OBJECTIVE To compare the accuracy of 2 motion sensors ( a pedometer and a multisensor ) in terms of step counting and estimation of energy expenditure ( EE ) in patients with chronic obstructive pulmonary disease ( COPD ) and in healthy elderly . DESIGN In this descriptive study , all participants wore both motion sensors while performing a treadmill walking protocol at 3 different speeds corresponding to 30 % , 60 % , and 100 % of the average speed achieved during a six-minute walk test . As criterion methods , EE was estimated by indirect calorimetry , and steps were registered by videotape . SETTING Research laboratory at a university hospital . PARTICIPANTS Patients with COPD ( n=30 ; 17 men ; mean age + /- SD , 67+/-8 y ; mean forced expiratory volume in the first second [ FEV(1 ) ] predicted + /- SD , 46%+/-17 % ; mean body mass index [ BMI ] + /- SD , 24+/-4 kg.m(2 ) ) and matched healthy elderly ( n=30 ; 15 men ; mean age + /- SD , 68+/-7 y ; mean FEV(1 ) predicted + /- SD , 104%+/-21 % ; mean BMI + /- SD , 25+/-3 kg.m(2 ) ) . INTERVENTIONS Not applicable . MAIN OUTCOME MEASURE Step counting and EE estimation during a  treadmill walking protocol . RESULTS The pedometer was accurate for step counting and EE estimation in both patients with COPD and healthy elderly at the higher speed . However , it showed significant underestimation at the 2 slower speeds in both groups . The multisensor did not detect steps accurately at any speed , although it accurately estimated EE at all speeds in healthy elderly and at the intermediate and higher speeds in patients with COPD . CONCLUSIONS In both patients with COPD and healthy elderly , the multisensor showed better EE estimates during most walking speeds than the pedometer . Conversely , for step counting , accuracy is observed only with the pedometer during the higher walking speed in both groups Combining accelerometry with heart rate monitoring has been suggested to improve energy estimates , however , it remains unclear whether the single , currently existing commercially available device combining these data streams ( Actiheart ) provides improved energy estimates compared to simpler and less expensive accelerometry-only devices . The purpose of this study was to compare the validity of the heart rate ( HR ) , accelerometry ( ACC ) , and combined ACC/HR estimates of the Actiheart to the ACC estimates of the Actical during low and moderate intensity activities . Twenty-seven participants ( mean age 26.3 ± 7.3 ) wore an Actical , Actiheart and indirect calorimeter ( K4b2 ) while performing card playing , sweeping , lifting weights , walking and jogging activities . All estimates tended to underestimate energy , sometimes by substantial amounts . Viewed across all activities studied , there was no significant difference in the ability of the waist-mounted Actical and torso-mounted Actiheart ( ACC , HR , ACC/HR ) estimates to predict energy expenditure . However , the Actiheart provided significantly better estimates than the Actical for the activities in which acceleration of the pelvis is not closely related to energy expenditure ( card playing , sweeping , lifting weights ) and the Actical provided significantly better estimates for level walking and level jogging . Similar to a previous study , the ACC component of the Actiheart was found to be the weakest predictor of energy suggesting it may be responsible for the failure of the combined ACC/HR estimate to equal or better the estimates derived solely from a waist mounted ACC device UNLABELLED It is suggested that triaxial accelerometers ( RT3 ) are superior to single-plane accelerometers for predicting energy expenditure ( EE ) . PURPOSE To compare the RT3 uniaxial and triaxial prediction of activity EE ( AEE ) during treadmill activities ( TM ) and activities of daily living ( ADL ) . METHODS Two hundred and twelve subjects ( aged 20 - 60 yr ) completed TM speeds of 1.34 , 1.56 , and 2.23 m x s(-1 ) at 0 % and 3 % grade s , stair ascent/descent , moving a box , and two r and omly assigned ADL . Subjects wore a portable indirect calorimeter to measure EE  to calculate AEE by subtracting resting metabolic rate . Acceleration counts in the vertical ( V ) , medial-lateral , and anterior-posterior planes were collected in a single RT3 secured to the hip . Predicted AEE ( RT3AEE ) was estimated from vector magnitude ( VM ) counts using a proprietary algorithm . A paired t-test compared RT3AEE versus AEE . The relationship among V and VM counts and AEE was examined using linear regression analyses . RESULTS RT3 overestimated AEE for all activities combined , overestimated for TM ( 9.0 % ) , and underestimated for ADL ( 34.3 % ; P < 0.001 ) . The R2 values between RT3AEE and AEE for TM and ADL were R2 = 0.78 and R2 = 0.15 , respectively . The RT3 underestimated activity with greater upper body movements by 24.4%-64.5 % ( P < 0.001 ) . V and VM counts were similarly related to AEE ( R2 = 0.35 ) and RT3AEE ( R2 = 0.83 - 0.89 ) . CONCLUSIONS Although the RT3 did not accurately predict AEE from accelerometer counts , stronger relationships existed between predicted and measured AEE for TM compared with ADL . Compared with V counts , using VM counts to predict AEE did not significantly improve the relationship between counts and AEE . Analytic techniques beyond linear regression with VM as a covariate or with counts from each axis entering the model separately may improve estimates of AEE from triaxial accelerometers OBJECTIVE The objective was to evaluate two accelerometers , the RT3 and the TriTrac-R3D for their ability to produce estimates of physical activity-related energy expenditure ( PAEE ) in overweight/obese adults . RESEARCH METHODS AND PROCEDURES PAEE estimates from both accelerometers were obtained in two experiments . In Experiment 1 , 13 overweight/obese subjects ( BMI 34.2+/-6.4 kg/m2 ) were monitored over 2 weeks in everyday life , PAEE being simultaneously measured by the doubly labeled water method ( DLW ) . In Experiment 2 , 8 overweight/obese subjects ( BMI 34.3+/-5.0 kg/m2 ) and 10 normal-weight subjects ( BMI 20.8+/-2.1 kg/m2 ) were monitored during a treadmill walking protocol , PAEE being simultaneously measured by indirect calorimetry . RESULTS In Experiment 1 , there was no significant difference between methods in mean PAEE ( DLW : 704+/-223 kcal/d , RT3 : 656+/-140 kcal/d , TriTrac-R3D 624+/-419 kcal/d ) . The relative difference between methods ( accelerometer vs. DLW ) was -17.1%+/-16.7 % for the RT3 and -20.0+/-44.6 % for the TriTrac-R3D . Correlation for PAEE between RT3 and DLW was higher than between TriTrac-R3D and DLW ( r=0.67 , p<0.05 and r=0.36 , p=0.25 , respectively ) . The 95 % confidence interval ( CI ) ( kcal/d ) of the mean difference between methods was large , amounting to -385 to 145 for the RT3 and -887 to 590 for the TriTrac-R3D . In Experiment 2 , both accelerometers were sensitive to the changes in treadmill speed , with no significant difference in mean PAEE between methods in overweight/obese subjects . CONCLUSIONS Although both accelerometers did not provide accurate estimates of PAEE at individual levels , the data suggest that RT3 has the potential to assess PAEE at group levels in overweight/obese subjects Background —The six-minute walk test ( 6MWT ) and cardiopulmonary exercise testing ( CPET ) are the 2 testing modalities most broadly used for assessing functional limitation in patients with heart failure ( HF ) . A comprehensive comparison on clinical and prognostic validity of the 2 techniques has not been performed and is the aim of the present investigation . Methods and Results —Two hundred fifty-three patients diagnosed with systolic ( n=211 ) or diastolic ( n=42 ) HF ( age : 61.9±10.1 years ; New York Heart Association Class : 2.2±0.78 ) underwent a 6MWT and a symptom-limited CPET evaluation and were prospect ively followed up . During the 4-year tracking period , there were 43 cardiac-related deaths with an annual cardiac mortality rate of 8.7 % . The 6MWT distance correlated with CPET-derived variables ( ie , peak Vo2 , Vo2 at anaerobic threshold , and Ve/Vco2 slope ) and was significantly reduced in proportion with lower peak Vo2 and higher Ve/Vco2 slope classes and presence of an exercise oscillatory breathing ( EOB ) pattern ( P<0.01 ) . However , no significant differences were observed in distance covered between survivors and nonsurvivors ( 353.2±95.8 m versus 338.5±76.4 m ; P = NS ) . At univariate and multivariate Cox proportional analyses , the association of the 6MWT distance with survival was not significant either as a continuous or dicotomized variable ( ≤300 m ) . Conversely , CPET-derived variables emerged as prognostic with the strongest association found for EOB ( systolic HF ) and Ve/Vco2 slope ( entire population with HF and patients with a 6MWT≤300 m ) . Conclusions —The 6MWT is confirmed to be a simple and reliable first-line test for quantification of exercise intolerance in patients with HF . However , there is no supportive evidence for its use as a prognostic marker in alternative to or in conjunction with CPET-derived variables PURPOSE We established accelerometer count ranges for the Computer Science and Applications , Inc. ( CSA ) activity monitor corresponding to commonly employed MET categories . METHODS Data were obtained from 50 adults ( 25 males , 25 females ) during treadmill exercise at three different speeds ( 4.8 , 6.4 , and 9.7 km x h(-1 ) ) . RESULTS Activity counts and steady-state oxygen consumption were highly correlated ( r = 0.88 ) , and count ranges corresponding to light , moderate , hard , and very hard intensity levels were < or = 1951 , 1952 - 5724 , 5725 - 9498 , > or = 9499 cnts x min(-1 ) , respectively . A model to predict energy expenditure from activity counts and body mass was developed using data from a r and om sample of 35 subjects ( r2 = 0.82 , SEE = 1.40 kcal x min(-1 ) ) . Cross validation with data from the remaining 15 subjects revealed no significant differences between actual and predicted energy expenditure at any treadmill speed ( SEE = 0.50 - 1.40 kcal x min(-1 ) ) . CONCLUSIONS These data provide a template on which patterns of activity can be classified into intensity levels using the CSA accelerometer PURPOSE To compare field measures of average daily energy expenditure ( ADEE ) against criterion data by the doubly labeled water method ( DLW ) in overweight women . METHODS The subject were 20 overweight ( BMI 29.9 + a- 3.0 kg.m-2 ) premenopausal women .  Energy expenditure was measured by DLW and by the factorial method ( activity diary , two techniques differing by method to obtain resting energy expenditure , REE ) , heart-rate monitoring ( HR , two techniques differing by the FLEX-point to discriminate sedentary and activity HR ) , accelerometer , and pedometer . RESULTS The ADEE(DLW ) was 10.26 + a- 1.1 MJ.d-1 . The mean bias ( ADEE by the alternative minus ADEE(DLW ) was smallest for the accelerometer ( + 0.08 + a- 1.63 MJ ) and HR-FLEX10 ( + 0.11 + a- 1.67 MJ ) . The HR-FLEX(0 ) technique ( lower FLEX-point ) overestimated ADEE by + 1.18 ( + a- 1.97 MJ ) . However , the r and om error ( SD of bias ) was smaller for both factorial techniques ( REE measured : -0.48 + 2- 0.81 MJ ; REE calculated from the WHO equation : -0.22 + 2- 0.88 MJ ) . CONCLUSION The results show that simple factorial methods may assess ADEE with small r and om errors in population with a rather narrow range of physical activity . The accelerometer and HR with the higher FLEX-point have comparable results with smaller bias but larger r and om error compared with the factorial techniques PURPOSE This study aim ed to predict human energy expenditure and activity type using a miniature lightweight ear-worn inertia sensor and a novel pattern recognition algorithm for activity detection . METHODS This study used a protocol of 11 activities of daily living : lying down , st and ing , computer work , vacuuming , stairs , slow walking , brisk walking , slow running , fast running , cycling , and rowing .  Subjects included 25 healthy r and omized subjects ( 18 males and 7 females ) . Each participant wore the ear sensor to record posture and linear acceleration  , as well as the Cosmed K4b system for indirect calorimetry . The main outcome measure was the continuous energy expenditure per minute prediction for both task-known and task-blind estimation . RESULTS The values for METs predicted using the proposed algorithm and the measured METs using the K4b showed good agreement with low values for the systematic bias ( lying down=0.01 , st and ing=-0.02 , computer work=-0.04 , vacuuming=-0.17 , stairs=-0.02 , slow walking=0.01 , fast walking=0.04 , slow running=0.14 , fast running=-0.35 , cycling=0.32 , and rowing=0.10 ) . For task-blind prediction , the agreement between predicted and measured METs is also good with low values of the systematic bias ( lying down=0.11 , st and ing=0.14 , computer work=-0.06 , vacuuming=0.47 , stairs=-0.47 , slow walking=0.53 , fast walking=-0.11 , slow running=0.83 , fast running=-1.18 , cycling=0.31 , and rowing=-0.67 ) . Activity is also well predicted ( for task-blind prediction ) with an overall success rate of 88.99 % and individual correct classification rates of lying down=89.62 % , st and ing/computer work=99.10 % , vacuuming=76.60 % , stairs=89.13 % , walking=85.11 % , running=98.96 % , and cycling=79.79 % . CONCLUSIONS The ear-worn sensor presented in this work is a novel lightweight device that can be used to predict energy expenditure for a range of activities without behavior interference or modification
target: 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 .
background: 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 .