Measurement Of Energy Expenditure Research Articles

How do guideline recommended energy targets compare with measured energy expenditure in critically ill adults with obesity: A systematic literature review

Critically ill patients with obesity have unique and complex nutritional needs, with clinical practice guidelines conflicting regarding recommended energy targets. The aim of this systematic review was to 1) describe measured resting energy expenditure (mREE) reported in the literature and; 2) compare mREE to predicted energy targets using the European (ESPEN) and American (ASPEN) guideline recommendations when indirect calorimetry is not available in critically ill patients with obesity. The protocol was registered apriori and literature was searched until 17th March, 2022. Original studies were included if they reported mREE using indirect calorimetry in critically ill patients with obesity (BMI≥30kg/m2). Group-level mREE data was reported as per the primary publication using mean±standard deviation or median [interquartile range]. Where individual patient data was available, Bland-Altman analysis was used to assess mean bias (95% limits of agreement) between guideline recommendations and mREE targets (i.e. ASPEN for BMI 30-50, 11-14kcal/kg actual weight compared to 70% mREE and ESPEN 20-25kcal/kg adjusted weight compared to 100% mREE). Accuracy was assessed by the percentage (%) of estimates within ±10% of mREE targets. After searching 8019 articles, 24 studies were included. mREE ranged from 1607±385 to 2919 [2318-3362]kcal and 12-32kcal/actual body weight. For the ASPEN recommendations of 11-14kcal/kg, a mean bias of-18% (-50% to+13%) and 4% (-36% to+44%) was observed, respectively (n=104). For the ESPEN recommendations 20-25kcal/kg, a bias of-22% (-51% to+7%) and-4% (-43% to+34%), was observed, respectively (n=114). The guideline recommendations were able to accurately predict mREE targets on 30%-39% occasions (11-14kcal/kg actual) and 15%-45% occasions (20-25kcal/kg adjusted), for ASPEN and ESPEN recommendations, respectively. Measured energy expenditure in critically ill patients with obesity is variable. Energy targets generated using predictive equations recommended in both the ASPEN and ESPEN clinical guidelines have poor agreement with mREE and are frequently not able to accurately predict within ±10% of mREE, most commonly underestimating energy needs.

The 13C-bicarbonate technique as a tool for measurement of energy expenditure in overweight dogs undergoing body weight reduction and the effect of different dietary composition.

Changes in body size and composition, i.e., body weight (BW) gain or loss, affect the daily energy expenditure (EE). To ensure an appropriate BW reduction and to find an efficient strategy to reduce and maintain a target BW, regular evaluations and adjustments of energy allowance are important. This study aimed to provide a detailed knowledge about the possible changes in resting EE using the oral 13C-bicarbonate technique (o13CBT) as a research tool in 16 overweight pet dogs undergoing BW reduction. Dietary composition (i.e., in % of dry matter [DM] being a high protein [33.3], low fat [9.6], and high crude fiber [18.0] diet [LFHFibre], and a high protein [37.9], high fat [52.0], carbohydrate-free diet [HFat]) during 16 wk of energy restriction were evaluated regarding effects on resting EE, rate of BW reduction, body composition, and plasma concentrations of metabolic hormones involved in energy metabolism and appetite regulation. The mean BW loss was higher (P < 0.05) for the dogs fed the LFHFibre diet (1.1%/wk) than that for dogs fed the HFat diet (0.8%/wk), but the total BW reduction of 14.6% and 12.0% of initial BW did not differ significantly (P > 0.05). Resting EE was lower (P < 0.02) after the BW reduction; 414 kJ (99 kcal)/kg BW0.75/d at the start (week 0) and 326 kJ (78 kcal)/kg BW0.75/d at the end (week 16) of the study. The BW reduction in both groups (P > 0.05) consisted of both fat mass (FM) and fat-free mass (FFM). Energy expenditure, calculated in relation to amount of FFM, was not significantly (P > 0.05) affected by BW reduction. Dietary composition did not significantly affect (P > 0.05) plasma concentrations of insulin, leptin, and ghrelin, and no effect (P > 0.05) of BW reduction was observed on hormone concentrations. In conclusion, the o13CBT proved to be a useful research method for studying short-term EE in overweight dogs. Even though all dogs lost BW, most dogs were still overweight at the end of the study. Due to a high individual variation among dogs, a longer experimental period with a larger sample size would be desirable.

Effects of modern military footwear on the oxygen costs of walking in US Army personnel

Warfighters complete strenuous physical activity on their feet throughout their military careers. While greater physiologic costs of walking have been demonstrated with older models of military combat boots versus running shoes, these quantitative differences may not be applicable for contemporary military footwear. The purpose of this study was to quantify and compare physiological responses to walking when wearing modern military combat boots versus running shoes. In this randomized, counterbalanced crossover experiment, 34 active military personnel (29 men and 5 women; age, 26 ± 7 years; height, 1.74 ± 0.08 m; body mass, 77.9 ± 15.1 kg) completed an incremental walking test (4.18–7.08 km.h−1) on separate visits in running shoes (mass, 0.6 ± 0.1 kg) and military combat boots (mass, 1.2 ± 0.3 kg). Oxygen uptake (V̇O2), carbon dioxide production (V̇CO2), heart rate (HR), respiration rate (RR), and metabolic energy expenditure (Ṁ) measurements were collected and averaged over the final minute of each walking speed. The oxygen costs of walking were 6–9% higher when wearing combat boots versus running shoes (p < 0.01 for each comparison). Other cardiorespiratory indicators of exercise intensity, specifically V̇CO2, Ṁ, HR, and RR, increased by 2.7–9.9% (p < 0.02 for each indicator). Walking in modern military combat boots incurs noticeably increased metabolic and cardiorespiratory strain as compared to walking in running shoes. These physiological consequences emphasize the trade-off between the intended versatility and protective characteristics of military footwear and the economy of traditional running shoes. This strain must be considered when selecting footwear to maximize warfighter health and performance during military exercise interventions.

Measuring energy expenditure using indirect calorimetry in long-stay intensive care patients – a feasibility study

Measuring energy expenditure using indirect calorimetry in long-stay intensive care patients – a feasibility study

Consumer wearable device-based measures of physical activity and energy expenditure in community-dwelling older adults with different levels of frailty: A STROBE compliant study.

Physical activity is important for positive health outcomes, and wearable activity devices are useful for tracking physical activity patterns and energy expenditure. This study investigated differences in, and correlations of, duration of physical activity according to activity intensity and energy expenditure among community-dwelling older adults with different levels of frailty. This cross-sectional study enrolled 88 adults older than 65 years from communities between June 2019 and January 2020. The participants were divided into non-frail, pre-frail, and frail groups according to the frailty criteria. Outcomes included the frailty score, duration of physical activity according to the intensity of activity (sedentary, light, fairly active, fairly to very active, and very active), and energy expenditure measured by a consumer wearable device. The duration of physical activity according to the intensity of activity and energy expenditure were compared among non-frail, pre-frail, and frail groups. In addition, linear correlation analysis was used to identify significant associations of objectively measured physical activity and energy expenditure with frailty. Non-frail older adults showed significantly longer daily duration of light to very active physical activity and increased energy expenditure compared to the frail group (P < .05). Additionally, non-frail older adults engaged in significantly more light and fairly to very active physical activity, and showed increased energy expenditure, compared to the pre-frail group (P < .05). The non-frail group showed a significantly lower duration of sedentary behavior compared to the pre-frail group. Correlation analysis showed that frailty was significantly associated with decreased light to very active physical activity and energy expenditure, as well as increased sedentary behavior (P < .05). This study provides evidence of differences in objectively measured physical activity and energy expenditure between frail and non-frail older adults, and reveals an association of frailty with physical activity and energy expenditure. Daily physical activity that exceeds low-intensity, low-energy expenditure activity should be encouraged among older adults with frailty.

Measuring human energy expenditure: public health application to counter inactivity

This article discusses the use of indirect calorimetry for the measurement of human energy expenditure. Quantification of energy expenditure during low efficiency walking (as depicted in the Monty Python sketch...

Effect of Exercise Using an Exoskeletal Hip-Assist Robot on Physical Function and Walking Efficiency in Older Adults.

Robotic technology has developed rapidly in recent years, and several robotic devices have been applied to improve physical, sensory, intellectual, psychological, and social functioning in the elderly and people with disabilities. In this study, we investigated the effects of EX1-assisted exercise in various environments on physical function, muscle strength, and walking efficiency in older adults. We designated four experimental conditions and randomly assigned participants to one of four groups: A (overground walking without an EX1), B (overground walking using the resistance mode of EX1), C (stair ascent using the assistance mode of EX1), and Group D (inclined treadmill walking using the assistance mode of EX1). A total of 60 community-dwelling elderly persons participated in 10 exercise intervention sessions for 4 weeks, and all participants were assessed before and after the exercise intervention. Physical function was measured by the 10-meter walk test for self-selected velocity (10MWT-SSV), short physical performance battery (SPPB), Berg balance scale (BBS), timed up and go (TUG), functional reach test (FRT), geriatric depression scale-short form (GDS-SF), and muscle strength of trunk and lower extremity. Cardiopulmonary metabolic energy efficiency was measured using a portable telemetric gas analyzer system. A significant increase in the 10MWT-SSV and TUG test was observed in groups B, C, and D. A statistically significant improvement in the SPPB and FRT was seen only in group D, and GDS-SF scores decreased significantly after exercise with an EX1 in groups B and D. Trunk and lower limb muscle strength increased more in the groups that exercised with EX1 assistance than those without an EX1, particularly in group B. The net metabolic energy costs and energy expenditure measurement during walking significantly improved in exercise groups C and D. The findings in this study support the application of the EX1 to physical activity and exercise to improve age-related changes in physical function, muscle strength, and walking efficiency among older adults. In addition, personalized exercise programs using different modes and training environments with an EX1 can enhance physical performance and walking efficiency in the elderly.

Relationships Between Resting Energy Expenditure and Transcranial Doppler Measurements in Patients With and Without Brain Death.

Introduction Brain metabolism deteriorates during brain death, suggesting that cerebral metabolic measurements could serve as a prognostic factor. The application of transcranial Doppler can be useful in evaluating patients evolving to brain death. Resting energy expenditure is lower than expected in patients with brain death, and this is caused by the decrease in cerebral blood flow and consequently lower oxygen supply. The primary aim of this retrospective study is to investigate the early metabolic changes in patients with clinical criteria of brain death and examine if these changes are related to a gradual decrease in blood flow velocities in the middle cerebral artery. Methods All consecutive patients from 1st June 2018 to 30th April 2022, admitted to the ICU with brain injury and a GCS ≤8, were included retrospectively in the study. Patients were allocated into two groups: Group A, patients without clinical signs of brain death (n = 32), and Group B, patients with brain death (n = 34). In each group, three sets of metabolic measurements were performed concomitantly with cerebral blood flow velocities using transcranial Doppler (a) upon admission to the ICU, (b) once hemodynamic stabilization was obtained, and (c) 48 hours after their hemodynamic stabilization or when brain death was confirmed by clinical criteria. Resting energy expenditure (REE) measurements were performed using a metabolic computer. Cerebral blood flow velocities were measured after a period of 30 min using a 2-MHZ 2D ultrasound probe. Results Brain-dead patients had a significant decrease in their metabolic parameters as the cerebral blood flow velocities recorded with the transcranial Doppler deteriorated, (REE Group A = 1667.65 ± 597 vs Group B = 1376.12 ± 615, p = 0.05 and REE predictedGroup A = 113.19 ± 44.9 vs Group B = 93.29 ± 41.5, p = 0.066 for measurement 1;REE Group A = 1844 ± 530.9 vs Group B = 1219.97 ± 489, p < 0.001 and REE predictedGroup A = 124.38 ± 39 vs Group B = 81.35 ± 30.4, p < 0.001 for measurement 2; REE Group A = 1750.97 ± 414, p < 0.001 and REE predicted Group A = 116.38 ± 19.2 vs Group B = 56.09 ± 19.6, p < 0.001 for measurement 3).Multiple stepwise regression analysis revealed a strong relationship between age, the worsening of the blood flow velocities pattern, and the decrease in REE (multiple R = 0.264, F = 5.55, p = 0.009).Furthermore, a statistically significant correlation was found between temperature and REE (correlation coefficient = 0.500, 0.674, 0.784 for measurements 1, 2, and 3, respectively, and p < 0.001 for all measures). Conclusions In brain-dead patients, the gradual decrease in cerebral blood flow leads to a decrease in REE as well as thermogenetic control. These changes can be detected early after the patient's admission to the ICU.

Objectively measured physical activity and cognition in cognitively normal older adults: A longitudinal analysis of the Australian Imaging Biomarkers and Lifestyle (AIBL) study

AbstractBackgroundPhysical inactivity is one of the greatest modifiable risk factors for dementia and research shows physical activity can delay cognitive decline in older adults. However, much of this research has used subjective physical activity data and a single follow‐up cognitive assessment. Further studies using objectively measured physical activity and comprehensive cognitive data measured at multiple timepoints are required.MethodsParticipants were 199 community‐dwelling cognitively normal older adults (68.7 5.9 years) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Actigraphy was used to measure physical activity at baseline, yielding measures of intensity (peak counts), total activity (total counts) and energy expenditure (kilocalories; k/cal). Cognitive function was assessed using a cognitive battery administered every 18‐months from baseline (3‐11 years follow‐up), yielding composite scores for episodic memory, executive function, attention and processing speed, and global cognition.ResultsHigher baseline energy expenditure predicted improvements in episodic memory and maintained global cognition over time (β = 0.011, SE = 0.005, p = 0.031; β = 0.009, SE = 0.004, p = 0.047, respectively). Both physical activity intensity and total activity predicted global cognition, such that those with higher peak and total counts had better cognition over time (β = 0.012, SE = 0.004, p = 0.005; β = 0.012, SE = 0.004, p = 0.005, respectively). Finally, higher total activity predicted improved episodic memory over time (β = 0.011, SE = 0.005, p = .022).ConclusionThese results suggest that physical activity is associated with preserved cognitive function over time, and that activity intensity may play an important role. This research further highlights the importance of early intervention to prevent cognitive decline and may aid in informing lifestyle interventions for dementia prevention.

Effects of a Modern Virtual Reality 3D Head-Mounted Display Exergame on Simulator Sickness and Immersion Under Specific Conditions in Young Women and Men: Experimental Study.

Many young adults do not reach the World Health Organization's minimum recommendations for the amount of weekly physical activity. The virtual reality 3D head-mounted display (VR 3D HMD) exergame is a technology that is more immersive than a typical exercise session. Our study considers gender differences in the experience of using VR games for increasing physical activity. The aim of this study was to examine the differences in the effects of VR 3D HMD gaming in terms of immersion, simulator sickness, heart rate, breathing rate, and energy expenditure during two 30-minute sessions of playing an exergame of increasing intensity on males and females. To examine the effects of the VR 3D HMD exergame, we experimented with 45 participants (23 males and 22 females) exercising with VR 3D HMD Oculus Quest 1, hand controllers, and Zephyr BioHarness 3.0. Players exercised according to the Audio Trip exergame. We evaluated the immersion levels and monitored the average heart rate, maximum heart rate, average breathing rate, maximum breathing rate, and energy expenditure in addition to simulator sickness during two 30-minute exergame sessions of increasing intensity. Audio Trip was well-tolerated, as there were no dropouts due to simulator sickness. Significant differences between genders were observed in the simulator sickness questionnaire for nausea (F2,86=0.80; P=.046), oculomotor disorders (F2,86=2.37; P=.010), disorientation (F2,86=0.92; P=.040), and total of all these symptoms (F2,86=3.33; P=.04). The measurements after the first 30-minute VR 3D HMD exergame session for all the participants showed no significant change compared to the measurements before the first 30-minute exergame session according to the total score. There were no gender differences in the immersion (F1,43=0.02; P=.90), but the measurements after the second 30-minute exergame session showed an increase in the average points for immersion in women and men. The increase in the level of immersion in the female group was higher than that in the male group. A significant difference between genders was observed in the average breathing rate (F2,86=1.44; P=.04), maximum breathing rate (F2,86=1.15; P=.047), and energy expenditure (F2,86=10.51; P=.001) measurements. No gender differences were observed in the average heart rate and maximum heart rate measurements in the two 30-minute sessions. Our 30-minute VR 3D HMD exergame session does not cause simulator sickness and is a very immersive type of exercise for men and women users. This exergame allows reaching the minimum recommendations for the amount of weekly physical activity for adults. The second exergame session resulted in simulator sickness in both groups, more noticeably in women, as reflected in the responses in the simulator sickness questionnaire. The gender differences observed in the breathing rates and energy expenditure measurements can be helpful when programming VR exergame intensity in future research.

It's electric! Measuring energy expenditure and perceptual differences between bicycles and electric-assist bicycles

BackgroundOne way to promote regular activity in communities is through bike share systems, which are increasingly integrating electric-assist pedal bikes (e-bikes). This study quantified the differences in energy expenditure, perceptions of difficulty, and acceleration between regular bikes and e-bikes in a bike share system. MethodsFirst, participants (n = 15) completed a bicycle maximal fitness test and had body composition assessed. Then, two, 1 hr long steady-state bicycle rides were completed at a local park, once on a regular bike and once on an e-bike. During each ride, heart rate and speed were continuously measured with a heart rate monitor. Participants reported perceived exertion at four intervals within each ride as well as perceived enjoyment, difficulty, and tiredness at the end of each ride. Paired t-tests were used to assess differences between the e-bike and regular bike share rides. ResultsParticipants exerted more energy at a greater percentage of maximum heart rate on the regular bike (mean = 69.6%) compared to the e-bike (mean = 61.5%, p = 0.006). Enjoyment was higher on the e-bike (mean = 4.6) than the regular bike (mean = 3.8; p = 0.009; 5-point Likert scale). Perceived exertion and difficulty were lower on the e-bike compared to the regular bike ride. ConclusionsE-bike share rides resulted in lower energy expenditure than regular bike share rides. Both bike rides resulted in moderate-intensity physical activity category, which can contribute to meeting national physical activity guidelines. In bike share systems, e-bikes may be attractive for integrating activity in daily routines since participants reported less difficulty and more enjoyment.

Non-invasive vagus nerve stimulation in a hungry state decreases heart rate variability

Vagus nerve signals from the gut to brain carry information about nutrients and drive food reward. Such signals are disrupted by consuming large amounts of high-calorie foods, necessitating greater food intake to elicit a similar neural response. Non‐invasive vagus nerve stimulation (nVNS) via a branch innervating the ear is a candidate treatment for obesity in humans. There is disagreement on the optimal location of nVNS in the ear for experimental and clinical studies. There are also no studies comparing nVNS in hungry and post-prandial states. We aimed to compare ear position(s) for nVNS and explore the effects of nVNS during hungry and post-prandial states on proxies for autonomic outflow (heart-rate variability) and efferent metabolism (gastric wave frequency and resting energy expenditure).In a within-subject design, 14 participants (10 women, on average 29.4 +/- 6.7 years old) received nVNS in four different locations (cymba conchae, tragus, earlobe, or tragus AND cymba conchae) on separate days. In each session, participants were asked to consume a palatable chocolate flavored milk. With electrography on the abdomen and indirect calorimetry in a canopy, we measured electro-cardiogram, electro-gastrogram and resting energy expenditure for 15 min before and at least 35 min after consumption of the palatable drink. We also collected ratings of the palatable drink and internal and other states.Pre-drink consumption (in a hungry state) we observed no differences in the effect of location of acute nVNS on resting energy expenditure and gastric wave measures. However, nVNS in cymba conchae decreases heart-rate variability (relative to sham) and ratings of how much participants want to consume the drink (relative to tragus AND cymba conchae and a trend relative to sham). After drink consumption and with continued nVNS, gastric wave frequency is unchanged, and resting energy expenditure increases regardless of stimulation location. Heart-rate variability decreases in all locations, except cymba conchae. We also observe a trend for an increase in gastric wave amplitude in late post-drink consumption time-points in cymba conchae. We observe no support for the combined stimulation of tragus AND cymba conchae being more effective than either of the individual locations.These results suggest that nVNS in the cymba conchae in a hungry state has a similar acute effect on vagal tone as food consumption: to decrease heart rate variability. This effect then negates the usual postprandial effects of a decrease in heart rate variability as seen in the other nVNS locations. These preliminary observations suggest that nVNS in cymba conchae may act primarily on vagal afferent autonomic (and only modestly on metabolic output) in a similar way as food consumption does.

A methodological and clinical approach to measured energy expenditure in the critically ill pediatric patient

The metabolic response to injury and stress is characterized initially by a decreased energy expenditure (Ebb phase) followed by an increased metabolic expenditure (Flow phase). Indirect calorimetry is a methodology utilized to measure energy expenditure and substrate utilization by measuring gas exchange in exhaled air and urinary nitrogen. The use of indirect calorimetry in critically ill patients requires precise equipment to obtain accurate measurements. The most recent guidelines suggested that measured energy expenditure by indirect calorimetry be used to determine energy requirements. This article reviews the methodological and clinical use of indirect calorimetry in critically ill pediatric patients.

Energy Expenditure Estimation in Children, Adolescents and Adults by Using a Respiratory Magnetometer Plethysmography System and a Deep Learning Model.

Purpose: Energy expenditure is a key parameter in quantifying physical activity. Traditional methods are limited because they are expensive and cumbersome. Additional portable and cheaper devices are developed to estimate energy expenditure to overcome this problem. It is essential to verify the accuracy of these devices. This study aims to validate the accuracy of energy expenditure estimation by a respiratory magnetometer plethysmography system in children, adolescents and adults using a deep learning model. Methods: Twenty-three healthy subjects in three groups (nine adults (A), eight post-pubertal (PP) males and six pubertal (P) females) first sat or stood for six minutes and then performed a maximal graded test on a bicycle ergometer until exhaustion. We measured energy expenditure, oxygen uptake, ventilatory thresholds 1 and 2 and maximal oxygen uptake. The respiratory magnetometer plethysmography system measured four chest and abdomen distances using magnetometers sensors. We trained the models to predict energy expenditure based on the temporal convolutional networks model. Results: The respiratory magnetometer plethysmography system provided accurate energy expenditure estimation in groups A (R2 = 0.98), PP (R2 = 0.98) and P (R2 = 0.97). The temporal convolutional networks model efficiently estimates energy expenditure under sitting, standing and high levels of exercise intensities. Conclusion: Our results proved the respiratory magnetometer plethysmography system’s effectiveness in estimating energy expenditure for different age populations across various intensities of physical activity.

The energetic cost of allostasis and allostatic load

Chronic psychosocial stress increases disease risk and mortality, but the underlying mechanisms remain largely unclear. Here we outline an energy-based model for the transduction of chronic stress into disease over time. The energetic model of allostatic load (EMAL) emphasizes the energetic cost of allostasis and allostatic load, where the “load” is the additional energetic burden required to support allostasis and stress-induced energy needs. Living organisms have a limited capacity to consume energy. Overconsumption of energy by allostatic brain-body processes leads to hypermetabolism, defined as excess energy expenditure above the organism’s optimum. In turn, hypermetabolism accelerates physiological decline in cells, laboratory animals, and humans, and may drive biological aging. Therefore, we propose that the transition from adaptive allostasis to maladaptive allostatic states, allostatic load, and allostatic overload arises when the added energetic cost of stress competes with longevity-promoting growth, maintenance, and repair. Mechanistically, the energetic restriction of growth, maintenance and repair processes leads to the progressive wear-and-tear of molecular and organ systems. The proposed model makes testable predictions around the physiological, cellular, and sub-cellular energetic mechanisms that transduce chronic stress into disease risk and mortality. We also highlight new avenues to quantify allostatic load and its link to health across the lifespan, via the integration of systemic and cellular energy expenditure measurements together with classic allostatic load biomarkers.

Minimally invasive biomarkers in human and non-human primate evolutionary biology: Tools for understanding variation and adaptation.

The use of minimally invasive biomarkers (MIBs - physiological biomarkers obtained from minimally invasive sample types) has expanded rapidly in science and medicine over the past several decades. The MIB approach is a methodological strength in the field of human and non-human primate evolutionary biology (HEB). Among humans and our closest relatives, MIBs provide unique opportunities to document phenotypic variation and to operationalize evolutionary hypotheses. This paper overviews the use of MIBs in HEB. Our objectives are to (1) highlight key research topics which successfully implement MIBs, (2) identify promising yet under-investigated areas of MIB application, and (3) discuss current challenges in MIB research, with suggestions for advancing the field. A range of MIBs are used to investigate focal topics in HEB, including energetics and life history variation/evolution, developmental plasticity, and social status and dominance relationships. Nonetheless, we identify gaps in existing MIB research on traits such as physical growth and gut function that are central to the field. Several challenges remain for HEB research using MIBs, including the need for additional biomarkers and methods of assessment, robust validations, and approaches that are standardized across labs and research groups. Importantly, researchers must provide better support for adaptation and fitness effects in hypothesis testing (e.g., by obtaining complementary measures of energy expenditure, demonstrating redundancy of function, and performing lifetime/longitudinal analyses). We point to continued progress in the use of MIBs in HEB to better understand the past, present, and future of humans and our closest primate relatives.

Measured Energy Expenditure Using Indirect Calorimetry in Post-Intensive Care Unit Hospitalized Survivors: A Comparison with Predictive Equations.

Actual energy needs after a stay in intensive care units (ICUs) are unknown. The aims of this observational study were to measure the energy expenditure (mEE) of ICU survivors during their post-ICU hospitalization period, and to compare this to the estimations of predictive equations (eEE). Survivors of an ICU stay ≥ 7 days were enrolled in the general ward during the first 7 days after ICU discharge. EE was measured using the Q-NRG calorimeter in canopy mode. This measure was compared to the estimated EE using the Harris–Benedict (HB) equation multiplied by a 1.3 stress factor, the Penn–State (PS) equation or the 30 kcal weight-based (WB) equation. A total of 55 adults were included (67.3% male, age 60 (52–67) y, body mass index 26.1 (22.2–29.7) kg/m2). Indirect calorimetry was performed 4 (3–6) d after an ICU stay of 12 (7–16) d. The mEE was 1682 (1328–1975) kcal/d, corresponding to 22.9 (19.1–24.2) kcal/kg/day. The eEE values derived using HB and WB equations were significantly higher than mEE: 3048 (1805–3332) and 2220 (1890–2640) kcal/d, respectively (both p < 0.001). There was no significant difference between mEE and eEE using the PS equation: 1589 (1443–1809) kcal/d (p = 0.145). The PS equation tended to underestimate mEE with a bias of −61.88 kcal and a wide 95% limit of agreement (−717.8 to 594 kcal). Using the PS equation, agreement within 15% of the mEE was found in 32/55 (58.2%) of the patients. In the present cohort of patients who survived a prolonged ICU stay, mEE was around 22–23 kcal/kg/day. In this post-ICU hospitalization context, none of the tested equations were accurate in predicting the EE measured by indirect calorimetry.

Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep Learning.

BackgroundCalorimetry is both expensive and obtrusive but provides the only way to accurately measure energy expenditure in daily living activities of any specific person, as different people can use different amounts of energy despite performing the same actions in the same manner. Deep learning video analysis techniques have traditionally required a lot of data to train; however, recent advances in few-shot learning, where only a few training examples are necessary, have made developing personalized models without a calorimeter a possibility.ObjectiveThe primary aim of this study is to determine which activities are most well suited to calibrate a vision-based personalized deep learning calorie estimation system for daily living activities.MethodsThe SPHERE (Sensor Platform for Healthcare in a Residential Environment) Calorie data set is used, which features 10 participants performing 11 daily living activities totaling 4.5 hours of footage. Calorimeter and video data are available for all recordings. A deep learning method is used to regress calorie predictions from video.ResultsModels are personalized with 32 seconds from all 11 actions in the data set, and mean square error (MSE) is taken against a calorimeter ground truth. The best single action for calibration is wipe (1.40 MSE). The best pair of actions are sweep and sit (1.09 MSE). This compares favorably to using a whole 30-minute sequence containing 11 actions to calibrate (1.06 MSE).ConclusionsA vision-based deep learning energy expenditure estimation system for a wide range of daily living activities can be calibrated to a specific person with footage and calorimeter data from 32 seconds of sweeping and 32 seconds of sitting.

The Apple Watch for Monitoring Mental Health-Related Physiological Symptoms: Literature Review.

BackgroundAn anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts.ObjectiveThis literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment.MethodsA literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch.ResultsA total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep.ConclusionsThe results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.

Calibration of an Accelerometer Activity Index among Older Women and Its Association with Cardiometabolic Risk Factors.

Traditional summary metrics provided by accelerometer device manufacturers, known as counts, are proprietary and manufacturer specific, making them difficult to compare studies using different devices. Alternative summary metrics based on raw accelerometry data have been introduced in recent years. However, they were often not calibrated on ground truth measures of activity-related energy expenditure for direct translation into continuous activity intensity levels. Our purpose is to calibrate, derive, and validate thresholds among women 60 years and older based on a recently proposed transparent raw data based accelerometer activity index (AAI), and to demonstrate its application in association with cardiometabolic risk factors. We first built calibration equations for estimating metabolic equivalents (METs) continuously using AAI and personal characteristics using internal calibration data (n=199). We then derived AAI cutpoints to classify epochs into sedentary behavior and intensity categories. The AAI cutpoints were applied to 4,655 data units in the main study. We then utilized linear models to investigate associations of AAI sedentary behavior and physical activity intensity with cardiometabolic risk factors. We found that AAI demonstrated great predictive accuracy for METs (R2=0.74). AAI-based physical activity measures were associated in the expected directions with body mass index (BMI), blood glucose, and high density lipoprotein (HDL) cholesterol. The calibration framework for AAI and the cutpoints derived for women older than 60 years can be applied to ongoing epidemiologic studies to more accurately define sedentary behavior and physical activity intensity exposures which could improve accuracy of estimated associations with health outcomes.