human
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Purpose We performed a study to determine the best appropriate wearing site of a triaxial accelerometer at different exercise speeds . Material s and Methods We conducted an observational study with 66 healthy Korean adults ( 26 men and 40 women ) .  Resting metabolic rate ( RMR ) before exercise , physical activity-related energy expenditure ( PAEE ) by cardiorespiratory gas analyzer and Signal Vector Magnitude ( SVM ) were measured while wearing four triaxial accelerometers on four different sites ( wrist , waist , upper arm , and ankle ) at exercise speeds from 2 - 10 km/h . Results The mean RMR was 4.03 mL/kg/min and Actual METs ( oxygen consumption at different exercise speeds divided by individual RMR ) compared with the calculated METs ( oxygen consumption divided by 3.5 mL/kg/min ) showed relatively low value . The overall correlation between PAEE and SVM was highest when the accelerometer was worn on the wrist at low exercise speed ( r=0.751 , p<0.001 ) , waist at a moderate speed ( r=0.821 , p<0.001 ) , and ankle at a high speed ( r=0.559 , p<0.001 ) . Using regression analysis , it was shown that the ankle at a low speed ( R2=0.564 , p<0.001 ) , high speed ( R2=0.559 , p<0.001 ) , and the waist at a moderate speed ( R2=0.821 , p<0.001 ) were the best appropriate sites . Conclusion When measuring the PAEE and SVM at different exercise speeds , the ankle in low and high exercise speed , and waist in moderate speed are the most appropriate sites for an accelerometer Background We hypothesized that a fully automated mobile health ( mHealth ) intervention with tracking and texting components would increase physical activity . Methods and Results mActive enrolled smartphone users aged 18 to 69 years at an ambulatory cardiology center in Baltimore , Maryl and . We used sequential r and omization to evaluate the intervention 's 2 core components . After establishing baseline activity during a blinded run‐in ( week 1 ) , in phase I ( weeks 2 to 3 ) , we r and omized 2:1 to unblinded versus blinded tracking . Unblinding allowed continuous access to activity data through a smartphone interface . In phase II ( weeks 4 to 5 ) , we r and omized unblinded participants 1:1 to smart texts versus no texts . Smart texts provided smartphone‐delivered coaching 3 times/day aim ed at individual encouragement and fostering feedback loops by a fully automated , physician‐written , theory‐based algorithm using real‐time activity data and 16 personal factors with a 10 000 steps/day goal . Forty‐eight out patients ( 46 % women , 21 % nonwhite ) enrolled with a mean±SD age of 58±8 years , body mass index of 31±6 kg/m2 , and baseline activity of 9670±4350 steps/day .  Daily activity data capture was 97.4 % . The phase I change in activity was nonsignificantly higher in unblinded participants versus blinded controls by 1024 daily steps ( 95 % confidence interval [ CI ] , −580 to 2628 ; P=0.21 ) . In phase II , participants receiving texts increased their daily steps over those not receiving texts by 2534 ( 95 % CI , 1318 to 3750 ; P<0.001 ) and over blinded controls by 3376 ( 95 % CI , 1951 to 4801 ; P<0.001 ) . Conclusions An automated tracking‐texting intervention increased physical activity with , but not without , the texting component . These results support new mHealth tracking technologies as facilitators in need of behavior change drivers . Clinical Trial Registration URL : http:// Clinical Trials.gov/. Unique identifier : NCT01917812 Purpose : The SenseWear ™ Armb and is an activity monitor developed to improve lifestyle self-monitoring . Currently , few studies assess electronic self-monitoring and weight loss with a lifestyle intervention program . To our knowledge , only one study has used the SenseWear Armb and in combination with a lifestyle intervention to improve weight loss , and no studies have evaluated whether a self-monitoring intervention based solely on the armb and can promote weight loss . Consequently , the aims of the study were to assess weight loss from electronic self-monitoring , to compare these values to the lifestyle intervention and st and ard care groups , and to compare weight loss with lifestyle intervention with and without the armb and . Patients and methods : We recruited 197 sedentary overweight or obese adults ( age , 46.8 ± 10.8 years ; BMI , 33.3 ± 5.2 kg/m2 ) to participate in the 9-month study . Participants were r and omized into one of four weight loss groups : 1 ) the st and ard care group received a self-directed weight loss program , complete with an evidence -based weight loss manual ( st and ard care , n = 50 ) ; 2 ) a 14-week group-based behavioral weight loss program followed by weekly , biweekly , and monthly telephone counseling calls ( GWL , n = 49 ) ; 3 ) the use of the armb and to help improve lifestyle self-monitoring ( SWA alone , n = 49 ) ; or ( 4 ) the group-based behavioral weight loss program and follow-up telephone counseling calls plus the armb and ( GWL + SWA , n = 49 ) . All participants received the evidence -based weight loss manual at baseline . All measures were performed at baseline and months 4 and 9 . The primary outcomes were weight loss and waist circumference reduction . Results : This study is a well- design ed r and omized controlled study powered to detect a 0.5-kg weight loss and 0.6-cm waist circumference reduction in overweight and obese sedentary adults . Conclusion : Innovative technologies are providing lifestyle self-monitoring and weight loss tools . Utilizing these technologies may be an important step in improving the current obesity epidemic Background Ageing is associated with a decrease in physical activity . This decrease particularly occurs during specific transitional life stages . Especially during adolescence and young adulthood a steep decrease in physical activity is observed . Inactive people are often not aware of their inactivity . Providing feedback on the actual physical activity level by an activity monitor can increase awareness and may in combination with an individually tailored physical activity advice stimulate a physically active lifestyle . Methods In a r and omized controlled trial the effectiveness of providing an activity monitor in combination with a personal physical activity advice through the Internet will be examined . Outcome measures are level of physical activity , determinants of physical activity , quality of life , empowerment , aerobic fitness and body composition .  Participants are relatively inactive adolescents and young adults who are measured at baseline , after 3 months intervention and 5 months after the end of the intervention . In addition , facilitating and hindering factors for implementation of the intervention will be investigated . Discussion The use of a personal activity monitor in combination with web-based assisted individually tailored health promotion offers a good opportunity to work interactively with large groups of adolescents and young adults and provide them with advice based on their actual activity level . It has great potential to motivate people to change their behaviour and to our knowledge has not been evaluated before Background Physical activity ( PA ) reduces pain and improves functioning in people with knee osteoarthritis ( OA ) , but few people with the condition meet recommended PA guidelines . Successful intervention strategies to increase PA include goal setting , action planning , self-monitoring , and follow-up feedback from a healthcare professional . Recently developed consumer wearable activity trackers allow users to set activity goals , self-monitor daily goal -progress , and provide feedback on goal attainment . It is hypothesized that a multi-component physiotherapist-led intervention that includes a short ( 40-min ) education module , guided goal - setting and action planning , the use of a wristb and activity tracker , and weekly follow-up phone calls will lead to increased PA outcomes . Methods / design Thirty-six participants will be recruited from the community for a two-group pilot r and omized controlled trial with a stepped-wedge design using an intention-to-treat analysis . Computer-generated block r and omization will be performed using varying block sizes and a 1:1 allocation ratio . The 4-week intervention will be delivered immediately ( immediate-intervention group ) or after a 5-week delay ( delayed-intervention group ) . Outcome measures of pain and disability ( Knee Injury and OA Outcome Score ) , disease self-management ability ( Partners in Health Scale ) , and objective bouted moderate-to-vigorous PA and sedentary time ( BodyMedia SenseWear Mini Armb and ) will be collected at baseline ( week 0 ) and two follow-ups ( weeks 5 and 10 ) , for a total study duration of 11 weeks . Feasibility data relating to process , re source , management , and scientific elements of the trial will be collected . Outcome measure and feasibility data will be summarized , and an estimate of intervention efficacy will be obtained by regression model with planned comparisons . The trial began recruiting in February 2015 . To date , 34 subjects have been recruited . Discussion This study will evaluate the feasibility and preliminary efficacy of a novel intervention to promote  PA in people living with knee OA . The results will provide valuable information to inform a larger r and omized trial to assess intervention effectiveness . Trial registration Clinical Trials.gov Identifier : NCT02313506 ( registration date 8 December 2014 ) . First participant r and omized 20 February 2015 Background As adults age , their physical activity decreases and sedentary behavior increases , leading to increased risk of negative health outcomes .  Wearable electronic activity monitors have shown promise for delivering effective behavior change techniques . However , little is known about the feasibility and acceptability of non-Fitbit wearables ( Fitbit , Inc , San Francisco , California ) combined with telephone counseling among adults aged more than 55 years . Objective The purpose of our study was to determine the feasibility , acceptability , and effect on physical activity of an intervention combining a wearable physical activity monitor , tablet device , and telephone counseling  among adults aged 55 - 79 years . Methods Adults ( N=40 , aged 55 - 79 years , body mass index=25 - 35 , < 60 min of activity per week ) were r and omized to receive a 12-week intervention or to a wait list control . Intervention participants received a Jawbone Up24 monitor , a tablet with the Jawbone Up app installed , and brief weekly telephone counseling . Participants set daily and weekly step goals and used the monitor ’s idle alert to notify them when they were sedentary for more than 1 h. Interventionists provided brief counseling once per week by telephone .  Feasibility was measured using observation and study records , and acceptability was measured by self-report using vali date d items . Physical activity and sedentary time were measured using ActivPAL monitors following st and ard protocol s. Body composition was measured using dual-energy x-ray absorptiometry scans , and fitness was measured using a 6-min walk test . Results Participants were 61.48 years old ( SD 5.60 ) , 85 % ( 34/40 ) female , 65 % ( 26/40 ) white .  Average activity monitor wear time was 81.85 ( SD 3.73 ) of 90 days . Of the 20 Up24 monitors , 5 were reported broken and 1 lost . No related adverse events were reported . Acceptability items were rated at least 4 on a scale of 1 - 5 . Effect sizes for most outcomes were small , including stepping time per day ( d=0.35 ) , steps per day ( d=0.26 ) , sitting time per day ( d=0.21 ) , body fat ( d=0.17 ) , and weight ( d=0.33 ) . Conclusions The intervention was feasible and acceptable in this population . Effect sizes were similar to the sizes found using other wearable electronic activity monitors , indicating that when combined with telephone counseling , wearable activity monitors are a potentially effective tool for increasing physical activity and decreasing sedentary behavior . Trial registration Clinical trials.gov NCT01869348 ; https:// clinical trials.gov/ct2/show/NCT01869348 ( Archived by WebCite at http://www.webcitation.org/6odlIolqy Background Maintaining mobility in elderly persons has become a primary goal within healthcare services . In older adults , exercise programs significantly reduce the risk of falling and death . Long-lasting and high-intensive multi-component exercises are most effective . In a rehabilitation setting , self-regulated exercises are conventionally taught by physiotherapists , using h and outs . However , the adherence of elderly persons to executing these self-administered programs varies considerably . They are often considered tedious and boring , and thus prematurely stopped . The primary aim of this clinical trial is to determine whether elderly persons in a rehabilitation setting show higher adherence to self-regulated training when using exergames than when performing conventional exercises . The second objective is to explore which mode of exercise leads to greater improvement in balance performance . Methods / Design The study consists of a single blind , stratified , r and omized control trial with two parallel groups . Once included , study participants will be stratified according to their balance and computer skills and r and omly allocated to self-regulated training with conventional exercise programs or with exergames played with the Windows Kinect ® sensor and FitBit ® pedometer . In both groups , self-administered exercise programs will be taught by experienced physiotherapists and performed at the patient ’s own discretion during the ten days of intervention . The primary outcome is the performed daily training volume 
    Output:
    
agent
CONCLUSIONS Utilizing a consumer-based wearable activity tracker as either the primary component of an intervention or as part of a broader physical activity intervention has the potential to increase physical activity participation .
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Purpose We performed a study to determine the best appropriate wearing site of a triaxial accelerometer at different exercise speeds . Material s and Methods We conducted an observational study with 66 healthy Korean adults ( 26 men and 40 women ) .  Resting metabolic rate ( RMR ) before exercise , physical activity-related energy expenditure ( PAEE ) by cardiorespiratory gas analyzer and Signal Vector Magnitude ( SVM ) were measured while wearing four triaxial accelerometers on four different sites ( wrist , waist , upper arm , and ankle ) at exercise speeds from 2 - 10 km/h . Results The mean RMR was 4.03 mL/kg/min and Actual METs ( oxygen consumption at different exercise speeds divided by individual RMR ) compared with the calculated METs ( oxygen consumption divided by 3.5 mL/kg/min ) showed relatively low value . The overall correlation between PAEE and SVM was highest when the accelerometer was worn on the wrist at low exercise speed ( r=0.751 , p<0.001 ) , waist at a moderate speed ( r=0.821 , p<0.001 ) , and ankle at a high speed ( r=0.559 , p<0.001 ) . Using regression analysis , it was shown that the ankle at a low speed ( R2=0.564 , p<0.001 ) , high speed ( R2=0.559 , p<0.001 ) , and the waist at a moderate speed ( R2=0.821 , p<0.001 ) were the best appropriate sites . Conclusion When measuring the PAEE and SVM at different exercise speeds , the ankle in low and high exercise speed , and waist in moderate speed are the most appropriate sites for an accelerometer Background We hypothesized that a fully automated mobile health ( mHealth ) intervention with tracking and texting components would increase physical activity . Methods and Results mActive enrolled smartphone users aged 18 to 69 years at an ambulatory cardiology center in Baltimore , Maryl and . We used sequential r and omization to evaluate the intervention 's 2 core components . After establishing baseline activity during a blinded run‐in ( week 1 ) , in phase I ( weeks 2 to 3 ) , we r and omized 2:1 to unblinded versus blinded tracking . Unblinding allowed continuous access to activity data through a smartphone interface . In phase II ( weeks 4 to 5 ) , we r and omized unblinded participants 1:1 to smart texts versus no texts . Smart texts provided smartphone‐delivered coaching 3 times/day aim ed at individual encouragement and fostering feedback loops by a fully automated , physician‐written , theory‐based algorithm using real‐time activity data and 16 personal factors with a 10 000 steps/day goal . Forty‐eight out patients ( 46 % women , 21 % nonwhite ) enrolled with a mean±SD age of 58±8 years , body mass index of 31±6 kg/m2 , and baseline activity of 9670±4350 steps/day .  Daily activity data capture was 97.4 % . The phase I change in activity was nonsignificantly higher in unblinded participants versus blinded controls by 1024 daily steps ( 95 % confidence interval [ CI ] , −580 to 2628 ; P=0.21 ) . In phase II , participants receiving texts increased their daily steps over those not receiving texts by 2534 ( 95 % CI , 1318 to 3750 ; P<0.001 ) and over blinded controls by 3376 ( 95 % CI , 1951 to 4801 ; P<0.001 ) . Conclusions An automated tracking‐texting intervention increased physical activity with , but not without , the texting component . These results support new mHealth tracking technologies as facilitators in need of behavior change drivers . Clinical Trial Registration URL : http:// Clinical Trials.gov/. Unique identifier : NCT01917812 Purpose : The SenseWear ™ Armb and is an activity monitor developed to improve lifestyle self-monitoring . Currently , few studies assess electronic self-monitoring and weight loss with a lifestyle intervention program . To our knowledge , only one study has used the SenseWear Armb and in combination with a lifestyle intervention to improve weight loss , and no studies have evaluated whether a self-monitoring intervention based solely on the armb and can promote weight loss . Consequently , the aims of the study were to assess weight loss from electronic self-monitoring , to compare these values to the lifestyle intervention and st and ard care groups , and to compare weight loss with lifestyle intervention with and without the armb and . Patients and methods : We recruited 197 sedentary overweight or obese adults ( age , 46.8 ± 10.8 years ; BMI , 33.3 ± 5.2 kg/m2 ) to participate in the 9-month study . Participants were r and omized into one of four weight loss groups : 1 ) the st and ard care group received a self-directed weight loss program , complete with an evidence -based weight loss manual ( st and ard care , n = 50 ) ; 2 ) a 14-week group-based behavioral weight loss program followed by weekly , biweekly , and monthly telephone counseling calls ( GWL , n = 49 ) ; 3 ) the use of the armb and to help improve lifestyle self-monitoring ( SWA alone , n = 49 ) ; or ( 4 ) the group-based behavioral weight loss program and follow-up telephone counseling calls plus the armb and ( GWL + SWA , n = 49 ) . All participants received the evidence -based weight loss manual at baseline . All measures were performed at baseline and months 4 and 9 . The primary outcomes were weight loss and waist circumference reduction . Results : This study is a well- design ed r and omized controlled study powered to detect a 0.5-kg weight loss and 0.6-cm waist circumference reduction in overweight and obese sedentary adults . Conclusion : Innovative technologies are providing lifestyle self-monitoring and weight loss tools . Utilizing these technologies may be an important step in improving the current obesity epidemic Background Ageing is associated with a decrease in physical activity . This decrease particularly occurs during specific transitional life stages . Especially during adolescence and young adulthood a steep decrease in physical activity is observed . Inactive people are often not aware of their inactivity . Providing feedback on the actual physical activity level by an activity monitor can increase awareness and may in combination with an individually tailored physical activity advice stimulate a physically active lifestyle . Methods In a r and omized controlled trial the effectiveness of providing an activity monitor in combination with a personal physical activity advice through the Internet will be examined . Outcome measures are level of physical activity , determinants of physical activity , quality of life , empowerment , aerobic fitness and body composition .  Participants are relatively inactive adolescents and young adults who are measured at baseline , after 3 months intervention and 5 months after the end of the intervention . In addition , facilitating and hindering factors for implementation of the intervention will be investigated . Discussion The use of a personal activity monitor in combination with web-based assisted individually tailored health promotion offers a good opportunity to work interactively with large groups of adolescents and young adults and provide them with advice based on their actual activity level . It has great potential to motivate people to change their behaviour and to our knowledge has not been evaluated before Background Physical activity ( PA ) reduces pain and improves functioning in people with knee osteoarthritis ( OA ) , but few people with the condition meet recommended PA guidelines . Successful intervention strategies to increase PA include goal setting , action planning , self-monitoring , and follow-up feedback from a healthcare professional . Recently developed consumer wearable activity trackers allow users to set activity goals , self-monitor daily goal -progress , and provide feedback on goal attainment . It is hypothesized that a multi-component physiotherapist-led intervention that includes a short ( 40-min ) education module , guided goal - setting and action planning , the use of a wristb and activity tracker , and weekly follow-up phone calls will lead to increased PA outcomes . Methods / design Thirty-six participants will be recruited from the community for a two-group pilot r and omized controlled trial with a stepped-wedge design using an intention-to-treat analysis . Computer-generated block r and omization will be performed using varying block sizes and a 1:1 allocation ratio . The 4-week intervention will be delivered immediately ( immediate-intervention group ) or after a 5-week delay ( delayed-intervention group ) . Outcome measures of pain and disability ( Knee Injury and OA Outcome Score ) , disease self-management ability ( Partners in Health Scale ) , and objective bouted moderate-to-vigorous PA and sedentary time ( BodyMedia SenseWear Mini Armb and ) will be collected at baseline ( week 0 ) and two follow-ups ( weeks 5 and 10 ) , for a total study duration of 11 weeks . Feasibility data relating to process , re source , management , and scientific elements of the trial will be collected . Outcome measure and feasibility data will be summarized , and an estimate of intervention efficacy will be obtained by regression model with planned comparisons . The trial began recruiting in February 2015 . To date , 34 subjects have been recruited . Discussion This study will evaluate the feasibility and preliminary efficacy of a novel intervention to promote  PA in people living with knee OA . The results will provide valuable information to inform a larger r and omized trial to assess intervention effectiveness . Trial registration Clinical Trials.gov Identifier : NCT02313506 ( registration date 8 December 2014 ) . First participant r and omized 20 February 2015 Background As adults age , their physical activity decreases and sedentary behavior increases , leading to increased risk of negative health outcomes .  Wearable electronic activity monitors have shown promise for delivering effective behavior change techniques . However , little is known about the feasibility and acceptability of non-Fitbit wearables ( Fitbit , Inc , San Francisco , California ) combined with telephone counseling among adults aged more than 55 years . Objective The purpose of our study was to determine the feasibility , acceptability , and effect on physical activity of an intervention combining a wearable physical activity monitor , tablet device , and telephone counseling  among adults aged 55 - 79 years . Methods Adults ( N=40 , aged 55 - 79 years , body mass index=25 - 35 , < 60 min of activity per week ) were r and omized to receive a 12-week intervention or to a wait list control . Intervention participants received a Jawbone Up24 monitor , a tablet with the Jawbone Up app installed , and brief weekly telephone counseling . Participants set daily and weekly step goals and used the monitor ’s idle alert to notify them when they were sedentary for more than 1 h. Interventionists provided brief counseling once per week by telephone .  Feasibility was measured using observation and study records , and acceptability was measured by self-report using vali date d items . Physical activity and sedentary time were measured using ActivPAL monitors following st and ard protocol s. Body composition was measured using dual-energy x-ray absorptiometry scans , and fitness was measured using a 6-min walk test . Results Participants were 61.48 years old ( SD 5.60 ) , 85 % ( 34/40 ) female , 65 % ( 26/40 ) white .  Average activity monitor wear time was 81.85 ( SD 3.73 ) of 90 days . Of the 20 Up24 monitors , 5 were reported broken and 1 lost . No related adverse events were reported . Acceptability items were rated at least 4 on a scale of 1 - 5 . Effect sizes for most outcomes were small , including stepping time per day ( d=0.35 ) , steps per day ( d=0.26 ) , sitting time per day ( d=0.21 ) , body fat ( d=0.17 ) , and weight ( d=0.33 ) . Conclusions The intervention was feasible and acceptable in this population . Effect sizes were similar to the sizes found using other wearable electronic activity monitors , indicating that when combined with telephone counseling , wearable activity monitors are a potentially effective tool for increasing physical activity and decreasing sedentary behavior . Trial registration Clinical trials.gov NCT01869348 ; https:// clinical trials.gov/ct2/show/NCT01869348 ( Archived by WebCite at http://www.webcitation.org/6odlIolqy Background Maintaining mobility in elderly persons has become a primary goal within healthcare services . In older adults , exercise programs significantly reduce the risk of falling and death . Long-lasting and high-intensive multi-component exercises are most effective . In a rehabilitation setting , self-regulated exercises are conventionally taught by physiotherapists , using h and outs . However , the adherence of elderly persons to executing these self-administered programs varies considerably . They are often considered tedious and boring , and thus prematurely stopped . The primary aim of this clinical trial is to determine whether elderly persons in a rehabilitation setting show higher adherence to self-regulated training when using exergames than when performing conventional exercises . The second objective is to explore which mode of exercise leads to greater improvement in balance performance . Methods / Design The study consists of a single blind , stratified , r and omized control trial with two parallel groups . Once included , study participants will be stratified according to their balance and computer skills and r and omly allocated to self-regulated training with conventional exercise programs or with exergames played with the Windows Kinect ® sensor and FitBit ® pedometer . In both groups , self-administered exercise programs will be taught by experienced physiotherapists and performed at the patient ’s own discretion during the ten days of intervention . The primary outcome is the performed daily training volume 
    Output:
    