Accelerometry-based method for assessing energy expenditure in patients with diabetes during walking

Energy expenditure estimation during activities of daily living in middle-aged and older adults using an accelerometer integrated into a hearing aid

Background

Accelerometers were traditionally worn on the hip to estimate energy expenditure (EE) during physical activity but are increasingly replaced by products worn on the wrist to enhance wear compliance, despite potential compromises in EE estimation accuracy. In the older population, where the prevalence of hearing loss is higher, a new, integrated option may arise. Thus, this study aimed to investigate the accuracy and precision of EE estimates using an accelerometer integrated into a hearing aid and compare its performance with sensors simultaneously worn on the wrist and hip.

Methods

Sixty middle-aged to older adults (average age 64.0 ± 8.0 years, 48% female) participated. They performed a 20-min resting energy expenditure measurement (after overnight fast) followed by a standardized breakfast and 13 different activities of daily living, 12 of them were individually selected from a set of 35 activities, ranging from sedentary and low intensity to more dynamic and physically demanding activities. Using indirect calorimetry as a reference for the metabolic equivalent of task (MET), we compared the EE estimations made using a hearing aid integrated device (Audéo) against those of a research device worn on the hip (ZurichMove) and consumer devices positioned on the wrist (Garmin and Fitbit). Class-estimated and class-known models were used to evaluate the accuracy and precision of EE estimates via Bland-Altman analyses.

Results

The findings reveal a mean bias and 95% limit of agreement for Audéo (class-estimated model) of -0.23 ± 3.33 METs, indicating a slight advantage over wrist-worn consumer devices (Garmin: -0.64 ± 3.53 METs and Fitbit: -0.67 ± 3.40 METs). Class-know models reveal a comparable performance between Audéo (-0.21 ± 2.51 METs) and ZurichMove (-0.13 ± 2.49 METs). Sub-analyses show substantial variability in accuracy for different activities and good accuracy when activities are averaged over a typical day's usage of 10 h (+61 ± 302 kcal).

Discussion

This study shows the potential of hearing aid-integrated accelerometers in accurately estimating EE across a wide range of activities in the target demographic, while also highlighting the necessity for ongoing optimization efforts considering precision limitations observed across both consumer and research devices.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review

BACKGROUND

People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases.

METHODS

Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device.

RESULTS

One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness.

CONCLUSION

This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.

Does Accelerometry at the Centre of Mass Accurately Predict the Gait Energy Expenditure in Patients with Hemiparesis?

BACKGROUND

The aim of this study was to compare energy expenditure (EE) predicted by accelerometery (EEAcc) with indirect calorimetry (EEMETA) in individuals with hemiparesis.

METHODS

Twenty-four participants (12 with stroke and 12 healthy controls) performed a six-minute walk test (6MWT) during which EEMETA was measured using a portable indirect calorimetry system and EEACC was calculated using Bouten's equation (1993) with data from a three-axis accelerometer positioned between L3 and L4.

RESULTS

The median EEMETA was 9.85 [8.18;11.89] W·kg-1 in the stroke group and 5.0 [4.56;5.46] W·kg-1 in the control group. The median EEACC was 8.57 [7.86;11.24] W·kg-1 in the control group and 8.2 [7.05;9.56] W·kg-1 in the stroke group. The EEACC and EEMETA were not significantly correlated in either the control (p = 0.8) or the stroke groups (p = 0.06). The Bland-Altman method showed a mean difference of 1.77 ± 3.65 W·kg-1 between the EEACC and EEMETA in the stroke group and -2.08 ± 1.59 W·kg-1 in the controls.

CONCLUSIONS

The accuracy of the predicted EE, based on the accelerometer and the equations proposed by Bouten et al., was low in individuals with hemiparesis and impaired gait. This combination (sensor and Bouten's equation) is not yet suitable for use as a stand-alone measure in clinical practice for the evaluation of hemiparetic patients.

Estimating energy expenditure from accelerometer data in healthy adults and patients with type 2 diabetes

OBJECTIVE

The aim of this study was to develop specific prediction equations based on acceleration data measured at three body sites for estimating energy expenditure (EE) during static and active conditions in middle-aged and older adults with and without type 2 diabetes (T2D).

RESEARCH METHODS

Forty patients with T2D (age: 40-74 yr, body mass index (BMI): 21-29.4 kg·m-2) and healthy participants (age: 47-79 yr, BMI: 20.2-29.8 kg·m-2) completed trials in both static conditions and treadmill walking. For all trials, gas exchange was monitored using indirect calorimetry and vector magnitude was calculated from acceleration data measured using inertial measurement units placed to the participant's center of mass (CM), hip and ankle. Stepwise multiple regression analyses were conducted to select relevant variables to include in the three EE prediction equations, and three Monte Carlo cross-validation procedures were used to evaluate each separate equation.

RESULTS

Vector magnitude (p < 0.0001) and personal data (gender, diabetes status and BMI; p < 0.0001) were used to develop three linear prediction equations to estimate EE during static conditions and walking. Cross-validation revealed similar robust coefficients of determination (R2: 0.81 to 0.85) and small bias (mean bias: 0.008 to -0.005 kcal·min-1) for all three equations. However, the equation based on CM acceleration exhibited the lowest root mean square error (0.60 kcal·min-1 vs. 0.65 and 0.69 kcal·min-1 for the hip and ankle equations, respectively; p < 0.001).

CONCLUSION

The three equations based on acceleration data and participant characteristics accurately estimated EE during sedentary conditions and walking in middle-aged and older adults, with or without diabetes.