The need to accurately measure energy intake and expenditure in patients with systemic sclerosis.

Background: Malnutrition is common in systemic sclerosis and patients are frequently underweight. However, the balance between assessed dietary energy intake versus expenditure has been neglected to date. This study aimed to assess energy (dietary) intakes and expenditures and to compare discrepancies in systemic sclerosis. Methods: Thirty-six outpatients with systemic sclerosis completed the study. Demographics and clinical data were recorded. Functional questionnaires were completed. Predicted energy requirements were calculated. Over a consecutive 3-day period, patients completed an estimated food diary and wore a specialist energy expenditure monitor (SenseWear® Armband). Assessments of intake and expenditure were compared for individual patients, and the impact according to patient demographics, clinical manifestations and disease severity evaluated. Results: Energy intake did not correlate with predicted (s = 0.117; p = 0.511) or measured (s = -0.039; p = 0.825) expenditures. Predicted and measured energy expenditures correlated, but actual values differed for individuals (intraclass correlation = 0.62; 95% limits of agreement = -459 to 751 kcal). Respiratory involvement was negatively correlated with number of steps (s = -0.350; p = 0.04) and time spent lying (s = 0.333; p = 0.05). There was a significant correlation between body mass index and predicted versus measured energy discrepancy (s = 0.41; p = 0.02), and this discrepancy was greater with higher body mass indices. Conclusion: There was no correlation between intake and either predicted or measured energy expenditure. Predicted and measured energy expenditures were strongly correlated yet differed for the individual patient. In patients with systemic sclerosis, where energy expenditure must be accurately assessed, it should be directly measured.

Low-Cost Wearable Band Sensors of Surface Electromyography for Detecting Hand Movements.

Surface electromyography (sEMG) is a non-invasive measure of electrical activity generated due to muscle contraction. In recent years, sEMG signals have been increasingly used in diverse applications such as rehabilitation, pattern recognition, and control of orthotic and prosthetic systems. This study presents the development of a versatile multi-channel sEMG low-cost wearable band system to acquire 4 signals. In this case, the signals acquired with the proposed device have been used to detect hand movements. However, the WyoFlex band could be used in some sections of the arm or the leg if the section's diameter matches the diameter of the WyoFlex band. The designed WyoFlex band was fabricated using three-dimensional (3D) printing techniques employing thermoplastic polyurethane and polylactic acid as manufacturing materials. Then, the proposed wearable electromyographic system (WES) consists of 2 WyoFlex bands, which simultaneously allow the wireless acquisition of 4 sEMG channels of each forearm. The collected sEMG can be visualized and stored for future post-processing stages using a graphical user interface designed in Node-RED. Several experimental tests were conducted to verify the performance of the WES. A dataset with sEMG collected from 15 healthy humans has been obtained as part of the presented results. In addition, a classification algorithm based on artificial neural networks has been implemented to validate the usability of the collected sEMG signals.

Design and Development Armband Vital Sign Monitor for Health-Care Monitoring.

BACKGROUND: One of the vital organs that require regular check is heart. The representation of heart health can be identified through electrocardiogram (ECG) signals, blood pressure (BP), heart rate, and oxygen saturation (SpO2). Monitoring the heart condition needs to be regularly done to prevent heart attack that can occur suddenly and very quickly particularly for someone who has had a heart attack before. Nevertheless, it raises the problem of cost, time efficient, and flexibility. It takes a high cost and much time to perform this examination. A vital signal monitoring device is needed with low cost, wearable, accurate, and simple in use. METHODS: This research designs and develops a device and application for monitoring human vital signals including ECG, SpO2, BP, and heart rate. A multi-sensor system with a control unit was applied to the device which was then called the Armband Vital Sign Monitor. This device can be used to measure vital parameters simultaneously using multiplexing techniques programmed in the microcontroller. Armband vital sign monitor is also equipped with Bluetooth module as a communication media for further data processing and display. RESULTS: Armband vital sign monitor produces >99% accuracy in body temperature measurements, ±2 deviation values in SpO2 measurements, and systolic and diastolic deviations at ±3-8 mmHg. For EGC signals, tests are performed by comparing signals visually in graphical form, and EGC can be obtained properly as shown by the graph. CONCLUSION: In this study, an Armband vital sign device has been developed that can measure the body's vital parameters. The parameters which were measured included temperature, heart rate, BP, SpO2, and ECG. This device has small dimensions and can be put on the wrist. The device is also equipped with Bluetooth so monitoring can be conducted wirelessly.

Evolution of the Greater Manchester Nutrition and Hydration Programme.

Older adults in the community are at risk of malnutrition and dehydration. The present article aims to outline an intervention and a population-health approach to raise awareness of the importance of good nutrition and hydration in later life. This was addressed by developing strong partnership working, governance frameworks and local steering committees. Through the Greater Manchester Nutrition and Hydration Programme, 39 500 older people have been asked about appetite and weight loss and/or used the PaperWeight Armband to date. A total of 5586 people from this population were found to be at risk of malnutrition. All were provided resources, advice and signposting to address this issue. The gross fiscal return on investment over a 5-year period was 3.2-fold and the net present budget impact was £800 000. The long-term cashable fiscal return on investment was estimated at 2.69. This very promising approach has potential to enable older adults to extend their healthy life span and deliver cost savings to the health and care system.

Assessment of energy intake and total energy expenditure in a series of patients who have undergone oesophagectomy following neoadjuvant treatment.

BACKGROUND: Assessment of malnutrition and its consequences are important aspects of curative management of patients with oesophageal cancer. The objective of the present study was to assess total energy expenditure using SenseWear Armband Mini® (SWA) as well as energy and protein intake in oesophageal cancer patients submitted to modern multimodality therapy. MATERIAL AND METHODS: Twenty patients were recruited at the time of diagnosis of oesophageal cancer. All patients were amenable for curative intended treatment. Baseline measurement was conducted before start of neoadjuvant treatment and three additional measurements were performed: after the completion of neoadjuvant treatment, at three, and six months postoperatively. The patients carried the SWA for three consecutive days at each measurement period, allowing the measurement of the free-living total energy expenditure and physical activity level. Alongside, a three-day complete food diary was recorded for calculation of energy and protein intake. Body weight was measured at all four occasions and weight six months prior to baseline was reported by the patients. RESULTS: Body weight steadily and significantly decreased during the preoperative phase (p = 0.005 and p = 0.007 at 6 months before baseline and after neoadjuvant treatment, respectively). However, the greatest weight loss was observed at 3 months after surgery (mean = 5.6 kg, p ≤ 0.001), where after it stabilised. Mean energy intake per day was 2033 (1730-2336) kcal at baseline, and increased to 2236 (2012-2461) kcal (p = 0.012) after completion of neoadjuvant treatment. At 3 months after oesophagectomy the daily energy intake decreased to 1759 (1459-2059) kcal (p = 0.155) compared to baseline and regained baseline levels first at 6 months postoperatively. The same trend was observed regarding protein intake. The mean total daily energy expenditure was 2259 (2077-2440) kcal at baseline with no change after the neoadjuvant oncological treatment. A significant reduction in energy expenditure to 1929 (1754-2105) kcal (p = 0.004) compared to baseline was recorded at 3 months post oesophagectomy, which remained unchanged at six months after surgery. CONCLUSION: With the objective to achieve and maintain energy balance, focus must be on the patients' energy intake already at the time of diagnosis, with regular follow up throughout the neoadjuvant therapy phase and during the first 3 postoperative months.

Wearable Devices for Caloric Intake Assessment: State of Art and Future Developments.

BACKGROUND: The self-monitoring of caloric intake is becoming necessary as the number of pathologies related to eating increases. New wearable devices may help people to automatically record energy assumed in their meals. OBJECTIVE: The present review collects the released articles about wearable devices or method for automatic caloric assessments. METHOD: A literature research has been performed with PubMed, Google Scholar, Scopus and ClinicalTrials.gov search engines, considering released articles regarding applications of wearable devices in eating environment, from 2005 onwards. RESULTS: Several tools allow caloric assessment and food registration: wearable devices counting the number of bites ingested by the user, instruments detecting swallows and chewings, methods that analyse food with digital photography. All of them still require more validation and improvement. CONCLUSION: Automatic recording of caloric intake through wearable devices is a promising method to monitor body weight and eating habits in clinical and non-clinical settings, and the research is still going on.

Influence of chemotherapy on total energy expenditure in patients with gastrointestinal cancer: A pilot study.

OBJECTIVE: Resting energy expenditure (REE) and physical activity (PA) undergo variations during chemotherapy. The aim of this study was to use a metabolic Holter (SenseWear Armband [SWA]) to assess REE, total energy expenditure (TEE), and PA changes in patients undergoing chemotherapy to ensure the appropriate calorie intake. To our knowledge, this is the first study to do so. METHODS: Eight patients with gastrointestinal tumors and a Karnofsky performance status of >50 underwent evaluation of the body mass index; REE, TEE, metabolic equivalent, and sleep efficiency were evaluated by SWA. Fat-free mass and fat mass were measured by bioelectrical impedance analysis, muscle strength by handgrip, and dietary intake by food diary. All evaluations were performed before chemotherapy (T0), at mid-treatment (T1), and at the end of treatment (T2). A calorie-equivalent diet to the TEE was recommended to all patients. RESULTS: At T0, a body weight loss of 15.1 ± 7.2% in the previous 6 mo was observed in all patients. Two patients did not complete treatment. During chemotherapy, thanks to the nutritional counseling, the remaining patients increased their calorie intake (P = 0.006) and no significant change was observed in other parameters. The REE calculation measured by SWA was correlated to the Harris-Benedict formula (P ≤ 0.002). CONCLUSION: The present data excluded significant variations of REE and PA in the course of chemotherapy in patients who do not experience weight loss and who have a Karnofsky performance status of >50. Nutritional counseling based on SWA measurements is useful to support nutritional status in patients undergoing chemotherapy.

Evaluation of a smartphone food diary application using objectively measured energy expenditure.

BACKGROUND: Dietary assessment methods are limited in their ability to adequately measure food and beverage consumption. Smartphone applications may provide a novel method of dietary assessment to capture real-time food intake and the contextual factors surrounding eating occasions. The aim of this study is to evaluate the capability of a Smartphone meal diary app ("FoodNow") to measure food intake using a validated objective method for assessing energy expenditure among young adults. METHODS: Participants (18-30 years) used FoodNow over four non-consecutive days recording all eating occasions through a combination of written text, and/or optional images and voice recordings. A series of contextual questions were also completed. Participants wore the validated SenseWear Armband (BodyMedia Inc, USA) during the same period to measure free-living energy expenditure. Intra-class correlation coefficients (ICC) estimated the reliability of FoodNow to measure estimated energy intake compared to measured energy expenditure. RESULTS: Ninety participants (71 female, 19 male; mean age = 24.9 ± 4.1 years) were recruited to use the FoodNow app to record their eating occasions. Thirteen were excluded as they did not meet minimum requirements for number of reporting days (n = 3) or SenseWear Armband wear time (5 days of 11 h), while 21 participants were excluded after being identified as mis-reporters (Huang method). Among the remaining sample (n = 56), reliability between estimated energy intake and measured energy expenditure was high (ICC, 95% CI: 0.75, 0.61-0.84). CONCLUSIONS: FoodNow is a suitable method for capturing estimated energy intake data from young adults. Despite wide levels of agreement at the individual level (-3709 kJ to 2056 kJ), at the group level, FoodNow appears to have potential as a dietary assessment tool. This new dietary assessment method will offer an alternative and novel method of dietary assessment which is capable of collecting both estimated energy intake and contextual factors surrounding eating occasions. Information collected may be used to inform future public health messages or research interventions.

Evaluation of a non-invasive multisensor accelerometer for calculating energy expenditure in ventilated intensive care patients compared to indirect calorimetry and predictive equations.

Continuous measurement of resting energy expenditure (REE) in critically ill patients remains challenging but is required to prevent malnutrition. SenseWear Pro 3 Armband (SWA) is a research grade accelerometer for assessment of REE with the advantage of easy handling. In a prospective study we compared SWA with indirect calorimetry (IC) and predictive equations in critically ill, ventilated patients. REE was measured by SWA, IC and calculated by predictive formulas. Potential confounding factors that influence REE were also recorded. Results of SenseWear Armband and indirect calorimetry were compared using the Bland-Altman method. 34 ICU patients were investigated. SWA underestimated resting energy expenditure compared to IC with a mean bias of ΔREE = -253.6 ± 333.2 kcal, equivalent to -11.7 % (p = 0.025). This underestimation was seen in both, medical (-14.9 %) and surgical (-12.9 %) patients and the bias was greater in patients with fever (-19.0 %), tachycardia (-18.7 %) or tachypnea (-26.2 %). Differences were also noted when SWA was compared to predictive formulas. At present, SWA cannot be regarded as an alternative to indirect calorimetry. Individual measurements are often inaccurate and should be used with caution until improved algorithms, based on the results of this study, have been implemented.

Multi-instrument assessment of physical activity in female office workers.

OBJECTIVES: The aim of this study was to examine the multi-instrument assessment of physical activity in female office workers. MATERIAL AND METHODS: Fifty healthy women (age (mean ± standard deviation): 34.8±5.9 years, body height: 158±0.4 cm, body weight: 61.8±7.5 kg, body mass index: 24.6±2.7 kg/m2) workers from the same workplace volunteered to participate in the study. Physical activity was measured with the 7-day Physical Activity Assessment Questionnaire (7-d PAAQ), an objective multi-sensor armband tool, and also a waist-mounted pedometer, which were both worn for 7 days. RESULTS: A significant correlation between step numbers measured by armband and pedometer was observed (r = 0.735), but the step numbers measured by these 2 methods were significantly different (10 941±2236 steps/ day and 9170±2377 steps/day, respectively; p < 0.001). There was a weak correlation between the value of 7-d PAAQ total energy expenditure and the value of armband total energy expenditure (r = 0.394, p = 0.005). However, total energy expenditure values measured by armband and 7-d PAAQ were not significantly different (2081±370 kcal/ day and 2084±197 kcal/day, respectively; p = 0.96). In addition, physical activity levels (average daily metabolic equivalents (MET)) measured by armband and 7-d PAAQ were not significantly different (1.45±0.12 MET/day and 1.47±0.24 MET/day, respectively; p = 0.44). CONCLUSIONS: The results of this study showed that the correlation between pedometer and armband measurements was higher than that between armband measurements and 7-d PAAQ selfreports. Our results suggest that none of the assessment methods examined here, 7-d PAAQ, pedometer, or armband, is sufficient when used as a single tool for physical activity level determination. Therefore, multi-instrument assessment methods are preferable. Int J Occup Med Environ Health 2016;29(6):937-945.

School Day Energy Expenditure in Elementary School Children.

BACKGROUND: The purpose was to characterize energy expenditure (EE) during academic subjects and activities during an elementary school day. METHODS: Children in 2nd to 4th grades (N = 33) wore the SenseWear Armband (SWA) for 5 school days to measure EE. Teachers' logs were compared with SWA data to extract information about EE throughout the day. Energy expenditure was also compared among grades. RESULTS: After controlling for body mass, grade level was not a significant predictor of average daily caloric expenditure, F (2, 17.58) = .29, P = .75, ω(2) = .05. When comparing activities throughout the day, relative rates of EE differed significantly, Wilks' F (7, 23) = 52.2, P = .00, ηp(2) = .94, with PE and recess having higher EE. When academic subjects were compared (math, science, language arts), relative rate of EE was also significantly different, Wilks' F (2, 30) = 4.31, P = .02, ηp(2) = .22. For the full sample, relative rate EE was higher in science than in language arts. CONCLUSIONS: The school day provides opportunity for EE for children. These data support the potential benefit of active instruction in language arts as a method to increase school day EE.

Evaluation of a Portable Armband Device to Assess Resting Energy Expenditure in Patients With Anorexia Nervosa.

BACKGROUND: In women with anorexia nervosa (AN), resting energy expenditure (REE) is decreased due to reduced energy intake and severe underweight. The assessment of REE allows estimating individual metabolic downregulation and better understanding body weight regulatory mechanisms in severely underweight patients with AN. However, REE predictive equations are known to have considerable shortcomings in patients with AN. Our aim was to evaluate a portable armband device (SenseWear armband [SWA]; BodyMedia, Inc, Pittsburgh, PA) for the assessment of REE against the measurement with indirect calorimetry (IC) as the reference method. METHODS: We assessed REE simultaneously by IC and SWA in 50 women with AN at the start of inpatient therapy and calculated REE using 2 predictive equations. RESULTS: Reliable data for IC measurement were obtained for 34 patients (age: 27.0 ± 8.0 years; body mass index: 14.4 ± 2.0 kg/m²). REE assessed with SWA was overestimated by 23% ± 27% compared with REE measured by IC (1166 ± 174 vs 979 ± 198 kcal/d, P < .001). REE estimation with SWA gave an accurate prediction within 10% deviation of REE measured with IC in 35% of the patients. In contrast, REE calculated with 2 predictive equations underestimated REE measured with IC by -26% ± 17% and -5% ± 20%, respectively. CONCLUSIONS: A mean difference of 187 kcal/d between both techniques for the assessment of REE may be of methodological relevance. Therefore, SWA and IC are not interchangeable methods for the assessment of REE in underweight females with AN.

A Mobile Phone App for Dietary Intake Assessment in Adolescents: An Evaluation Study.

BACKGROUND: There is a great need for dietary assessment methods that suit the adolescent lifestyle and give valid intake data. OBJECTIVE: To develop a mobile phone app and evaluate its ability to assess energy intake (EI) and total energy expenditure (TEE) compared with objectively measured TEE. Furthermore, to investigate the impact of factors on reporting accuracy of EI, and to compare dietary intake with a Web-based method. METHODS: Participants 14 to 16 years of age were recruited from year nine in schools in Gothenburg, Sweden. In total, 81 adolescents used the mobile phone app over 1 to 6 days. TEE was measured with the SenseWear Armband (SWA) during the same or proximate days. Individual factors were assessed with a questionnaire. A total of 15 participants also recorded dietary intake using a Web-based method. RESULTS: The mobile phone app underestimated EI by 29% on a group level (P<.001) compared to TEE measured with the SWA, and there was no significant correlation between EI and TEE. Accuracy of EI relative to TEE increased with a weekend day in the record (P=.007) and lower BMI z-score (P=.001). TEE assessed with the mobile phone app was 1.19 times the value of TEE measured by the SWA on a group level (P<.001), and the correlation between the methods was .75 (P<.001). Analysis of physical activity levels (PAL) from the mobile phone app stratified by gender showed that accuracy of the mobile phone app was higher among boys. EI, nutrients, and food groups assessed with the mobile phone app and Web-based method among 15 participants were not significantly different and several were significantly correlated, but strong conclusions cannot be drawn due to the low number of participants. CONCLUSIONS: By using a mobile phone dietary assessment app, on average 71% of adolescents' EI was captured. The accuracy of reported dietary intake was higher with lower BMI z-score and if a weekend day was included in the record. The daily question in the mobile phone app about physical activity could accurately rank the participants' TEE.

Physical activity and energy expenditure during depressive episodes of major depression.

BACKGROUND: Recent data suggest a substantial association between physical activity and depressive symptoms, but there is a lack of research evaluating the physical activity levels in patients suffering from unipolar depression across different stages of disease in an objective way. The aim of the present pilot study was to objectively examine physical activity levels of this patient group compared to healthy controls. METHODS: Physical activity performance of 19 patients with major depressive episode and 19 healthy controls was assessed at three different time points using a multisensory armband device (SenseWear® Pro3 Armband) and was reported as total energy expenditure (TEE), active energy expenditure (EE), metabolic equivalents (METs), physical activity (PA) and time of lying down (LD), in each case over 24h. RESULTS: Over all measurements, depressive patients presented a significantly lower mean TEE and EE over 24h. Moreover, the patient group showed significantly shorter duration of PA and lower average MET over 24h. When depressive symptoms abated, physical activity parameters significantly increased in the patient group. Correlation analyses demonstrated a significant relation between depressive status/anhedonia and parameters of physical activity, especially in healthy subjects. LIMITATIONS: Results represented valid data for inpatients only. CONCLUSION: Acute unipolar depression was associated with a significantly lower level of physical activity and showed a significant increase in parallel to clinical improvement. Electronic monitoring of physical activity may be an additional tool for evaluating and controlling therapeutic effects.

Validity and reliability of Nike + Fuelband for estimating physical activity energy expenditure.

BACKGROUND: The Nike + Fuelband is a commercially available, wrist-worn accelerometer used to track physical activity energy expenditure (PAEE) during exercise. However, validation studies assessing the accuracy of this device for estimating PAEE are lacking. Therefore, this study examined the validity and reliability of the Nike + Fuelband for estimating PAEE during physical activity in young adults. Secondarily, we compared PAEE estimation of the Nike + Fuelband with the previously validated SenseWear Armband (SWA). METHODS: Twenty-four participants (n = 24) completed two, 60-min semi-structured routines consisting of sedentary/light-intensity, moderate-intensity, and vigorous-intensity physical activity. Participants wore a Nike + Fuelband and SWA, while oxygen uptake was measured continuously with an Oxycon Mobile (OM) metabolic measurement system (criterion). RESULTS: The Nike + Fuelband (ICC = 0.77) and SWA (ICC = 0.61) both demonstrated moderate to good validity. PAEE estimates provided by the Nike + Fuelband (246 ± 67 kcal) and SWA (238 ± 57 kcal) were not statistically different than OM (243 ± 67 kcal). Both devices also displayed similar mean absolute percent errors for PAEE estimates (Nike + Fuelband = 16 ± 13 %; SWA = 18 ± 18 %). Test-retest reliability for PAEE indicated good stability for Nike + Fuelband (ICC = 0.96) and SWA (ICC = 0.90). CONCLUSION: The Nike + Fuelband provided valid and reliable estimates of PAEE, that are similar to the previously validated SWA, during a routine that included approximately equal amounts of sedentary/light-, moderate- and vigorous-intensity physical activity.

Comparison of total energy expenditure assessed by two devices in controlled and free-living conditions.

The objective of this study was to evaluate the validity of total energy expenditure (TEE) provided by Actiheart and Armband. Normal-weight adult volunteers wore both devices either for 17 hours in a calorimetric chamber (CC, n = 49) or for 10 days in free-living conditions (FLC) outside the laboratory (n = 41). The two devices and indirect calorimetry or doubly labelled water, respectively, were used to estimate TEE in the CC group and FLC group. In the CC, the relative value of TEE error was not significant (p > 0.05) for Actiheart but significantly different from zero for Armband, showing TEE underestimation (-4.9%, p < 0.0001). However, the mean absolute values of errors were significantly different between Actiheart and Armband: 8.6% and 6.7%, respectively (p = 0.05). Armband was more accurate for estimating TEE during sleeping, rest, recovery periods and sitting-standing. Actiheart provided better estimation during step and walking. In FLC, no significant error in relative value was detected. Nevertheless, Armband produced smaller errors in absolute value than Actiheart (8.6% vs. 12.8%). The distributions of differences were more scattered around the means, suggesting a higher inter-individual variability in TEE estimated by Actiheart than by Armband. Our results show that both monitors are appropriate for estimating TEE. Armband is more effective than Actiheart at the individual level for daily light-intensity activities.

A smartphone-driven methodology for estimating physical activities and energy expenditure in free living conditions.

This paper introduces a function dedicated to the estimation of total energy expenditure (TEE) of daily activities based on data from accelerometers integrated into smartphones. The use of mass-market sensors such as accelerometers offers a promising solution for the general public due to the growing smartphone market over the last decade. The TEE estimation function quality was evaluated using data from intensive numerical experiments based, first, on 12 volunteers equipped with a smartphone and two research sensors (Armband and Actiheart) in controlled conditions (CC) and, then, on 30 other volunteers in free-living conditions (FLC). The TEE given by these two sensors in both conditions and estimated from the metabolic equivalent tasks (MET) in CC served as references during the creation and evaluation of the function. The TEE mean gap in absolute value between the function and the three references was 7.0%, 16.4% and 2.7% in CC, and 17.0% and 23.7% according to Armband and Actiheart, respectively, in FLC. This is the first step in the definition of a new feedback mechanism that promotes self-management and daily-efficiency evaluation of physical activity as part of an information system dedicated to the prevention of chronic diseases.

Validation of SenseWear Armband and ActiHeart monitors for assessments of daily energy expenditure in free-living women with chronic obstructive pulmonary disease.

To provide individually adapted nutritional support to patients with chronic obstructive pulmonary disease (COPD), objective and reliable methods must be used to assess patient energy requirements. The aim of this study was to validate the use of SenseWear Armband (SWA) and ActiHeart (AH) monitors for assessing total daily energy expenditure (TEE) and activity energy expenditure (AEE) and compare these techniques with the doubly labeled water (DLW) method in free-living women with COPD. TEE and AEE were measured in 19 women with COPD for 14 days using SWAs with software version 5.1 (TEESWA5, AEESWA5) or 6.1 (TEESWA6, AEESWA6) and AH monitors (TEEAH, AEEAH), using DLW (TEEDLW) as the criterion method. The three methods were compared using intraclass correlation coefficient (ICC) and Bland-Altman analyses. The mean TEE did not significantly differ between the DLW and SWA5.1 methods (-21 ± 726 kJ/day; P = 0.9), but it did significantly differ between the DLW and SWA6.1 (709 ± 667 kJ/day) (P < 0.001) and the DLW and AH methods (709 ± 786 kJ/day) (P < 0.001). Strong agreement was observed between the DLW and TEESWA5 methods (ICC = 0.76; 95% CI 0.47-0.90), with moderate agreements between the DLW and TEESWA6 (ICC = 0.66; 95% CI 0.02-0.88) and the DLW and TEEAH methods (ICC = 0.61; 95% CI 0.05-0.85). Compared with the DLW method, the SWA5.1 underestimated AEE by 12% (P = 0.03), whereas the SWA6.1 and AH monitors underestimated AEE by 35% (P < 0.001). Bland-Altman plots revealed no systematic bias for TEE or AEE. The SWA5.1 can reliably assess TEE in women with COPD. However, the SWA6.1 and AH monitors underestimate TEE. The SWA and AH monitors underestimate AEE.

Validity of a Multi-Sensor Armband for Estimating Energy Expenditure during Eighteen Different Activities.

PURPOSE: To examine the validity of an armband physical activity monitor in estimating energy expenditure (EE) over a wide range of physical activities. METHODS: 68 participants (mean age=39.5 ± 13.0 yrs) performed one of three routines consisting of six activities (approximately 10 min each) while wearing the armband and the Cosmed K4b2 portable metabolic unit. Routine 1 (n=25) involved indoor home-based activities, routine 2 (n=22) involved miscellaneous activities, and routine 3 (n=21) involved outdoor aerobic activities. RESULTS: Mean differences between the EE values in METs (criterion minus estimated) are as follows. Routine 1: watching TV (-0.1), reading (-0.1), laundry (0.1), ironing (-1.3), light cleaning (-0.4), and aerobics (0.4). Routine 2: driving (-0.6), Frisbee golf (-0.9), grass trimming (-0.5), gardening (-1.5), moving dirt with a wheelbarrow (-0.1), loading and unloading boxes (0.1); Routine 3: sidewalk walking (-1.0), track walking (-0.8), walking with a bag (-0.6), tennis (1.6), track running (2.2), and road running (2.1). The armband significantly overestimated EE during several light-to-moderate intensity activities such as driving (by 74%), ironing (by 70%), gardening (by 55%), light cleaning (by 15%), Frisbee golf (by 24%), and sidewalk walking (by 26%) (P<0.05). The arm band significantly underestimated high intensity activities including tennis (by 20%), and track or road running (by 20%). CONCLUSION: Although the armband provided mean EE estimates within 16% of the criterion for nine of the 18 activities, predictions for several activities were significantly different from the criterion. The armband prediction algorithms could be refined to increase the accuracy of EE estimations.

Energy expenditure and habitual physical activities in adolescent sprint athletes.

This study aimed to assess total energy expenditure (TEE) and specific habitual physical activities in adolescent sprint athletes. Two methods used to estimate TEE, an activity diary (AD) and SenseWear armband (SWA), were compared. Sixteen athletes (6 girls, 10 boys, mean age 16.5 ± 1.6 yr) simultaneously wore a SWA and completed an AD and food diary during one week. Basal energy expenditure as given by the SWA when taken off was corrected for the appropriate MET value using the AD. TEE as estimated by the AD and SWA was comparable (3196 ± 590 kcal and 3012 ± 518 kcal, p = 0.113) without day-to-day variations in TEE and energy expended in activities of high intensity. Daily energy intake (2569 ± 508 kcal) did not match TEE according to both the AD and SWA (respectively p < 0.001 and p = 0.007). Athletes were in a supine position for a longer time on weekend days than on week days and slept longer on Sundays. Athletes reported a longer time of high-intensive physical activities in the AD than registered by the SWA on 4 out of 7 days. In addition to specific sprint activities on 3 to 7 days per week, 11 out of 16 athletes actively commuted to school where they participated in sports once or twice per week. The AD and the SWA are comparable in the estimation of TEE, which appears realistic and sustainable. The SWA offers an appropriate and objective method in the assessment of TEE, sleeping and resting in adolescent athletes on the condition that detailed information is given for the times the armband is not worn. The AD offers activity specific information but relies on the motivation, compliance and subjectivity of the individual, especially considering high-intensive intermittent training. Key pointsThe activity diary and Sensewear armband provide comparable estimates of TEE in adolescent sprint athletes.A high inter-individual variation was observed in time spent in high-intensity physical activities, advocating an individual based assessment when coaching athletes.The activity diary is useful when detailed information on specific physical activities is desired. The Sensewear armband offers objective information on sleeping, resting, and physical activity duration.Wearing the Sensewear combined with reporting on activities when the Sensewear is not worn and when doing specific activities of interest results in more complete information.