Lack of Correlation between Accelerometers and Heart-Rate Monitorization during Exercise Session in Older Adults

Carbonell-Hernández, Laura; Pastor, Diego; Jiménez-Loaisa, Alejandro; Ballester-Ferrer, Juan Arturo; Montero-Carretero, Carlos; Cervelló, Eduardo

doi:10.3390/ijerph17155518

Cited by 5 publications

(5 citation statements)

References 25 publications

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“…Gait training using parallel bars or on a treadmill with minimal arm swing may also have been poorly detected. A study on the relationship between accelerometer and HR monitor measurements in older adults during exercise sessions found that an accelerometer placed on the hip failed to capture exercises involving balance and neuromotor function ( 31 ). This suggests that the position of the accelerometer should consider the specific exercises performed during rehabilitation sessions.…”

Section: Discussionmentioning

confidence: 99%

Comparison of motion sensor and heart rate monitor for assessment of physical activity intensity in stroke outpatient rehabilitation sessions: an observational study

Goncalves,

Mandigout,

Le Bourvellec

et al. 2024

JRM

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Objective: To compare the estimation of time spent on 4 categories of physical activity intensity (sedentary behaviour, light physical activity, moderate physical activity, and vigorous physical activity) between a motion sensor and a heart rate monitor during a stroke outpatient rehabilitation session. Design: A multicentre cross-sectional observational study. Subjects/Patients: Participants with stroke (> 6 months) undergoing outpatient rehabilitation sessions. Methods: Participants wore the SenseWear Armband motion sensor and the Polar H10 heart rate monitor during 2 rehabilitation sessions. The times estimated by each device were compared using a generalized linear mixed model and post-hoc tests. Results: Ninety-nine participants from 29 clinics were recruited and data from 146 sessions were included in the analysis. The estimated times depended on the devices and the physical activity intensity category (F = 135, p < 0.05). The motion sensor estimated more time spent in sedentary behaviour and less time spent in moderate physical activity and vigorous physical activity than the heart rate monitor. Conclusion: The motion sensor and heart rate monitor provide different estimates of physical activity intensity during stroke rehabilitation. Further research is needed to establish the most appropriate device for each physical activity category.

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Section: Discussionmentioning

confidence: 99%

Comparison of motion sensor and heart rate monitor for assessment of physical activity intensity in stroke outpatient rehabilitation sessions: an observational study

Goncalves,

Mandigout,

Le Bourvellec

et al. 2024

JRM

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“…It involves three key components, namely, health, participation, and security, which have been extensively studied by academics. Health refers to lowering disease induced by ageing, hence, a well-designed physical activity location is a crucial strategy to protect the health of older adults [14]. Participation signifies that older adults may engage in activities according to their abilities, needs, and preferences, and may even contribute to society [15].…”

Section: Literature Reviewmentioning

confidence: 99%

Ageing Suitability Evaluation of Residential Districts Based on Active Ageing Theory

Liu

et al. 2023

Buildings

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Residential districts, the primary locations for older adults, struggle to satisfy the needs of the rising older population due to ageing infrastructure, etc. China has begun to focus on this issue through the popularization of approaches such as active ageing theory (AAT), and has implemented ageing suitability renovations. Meanwhile, recent evaluation models failed to validate their logic and standardization. The current evaluation models prioritize the indoor environment above the external environment. Therefore, this study attempts to provide a comprehensive evaluation model of the ageing suitability of residential districts. First, 23 indicators of ageing suitability were identified by a systematic literature review and expert interviews; next, the indicators were categorized using the active ageing theory. Second, the grey correlation analysis approach was used to calculate the weights of evaluation indicators, and the existing evaluation criteria were incorporated to formulate the evaluation criteria for the project. Eventually, the evaluation model was constructed. Finally, the feasibility of the model was validated by a case study. The findings of this study can help provide directions for the future renovation of old residential districts (for example, the activity area should be over 200 m2) and the construction of suitable houses for older adults, such as the installation of a continuous handrail, to alleviate the increasingly grave problem of ageing and promote the development of the pension industry.

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“…As a result, alternative metrics like “activity count,” moving SD of acceleration (MSDA), or root mean square might be more appropriate for quantifying activity in certain contexts [ 15 - 17 ]. Prior studies have shown that heart rate and acceleration-measured activity values can behave differently [ 18 ], and that these indices can complement each other in estimating energy expenditure [ 19 , 20 ]. Thus, simultaneous measurement of these indices may offer valuable insights into the activity patterns of patients who had strokes.…”

Section: Introductionmentioning

confidence: 99%

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study

Mizuno,

Ogasawara,

Mukaino

et al. 2024

JMIR Form Res

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Background Motor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities. Objective This study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity. Methods In this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients’ daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks. Results A significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=–0.41, P=.21) or 4 weeks post admission (ρ=–0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=–0.82, P=.002) and 4 weeks post admission (ρ=–0.73, P=.01). Conclusions Inpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

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Lack of Correlation between Accelerometers and Heart-Rate Monitorization during Exercise Session in Older Adults

Cited by 5 publications

References 25 publications

Comparison of motion sensor and heart rate monitor for assessment of physical activity intensity in stroke outpatient rehabilitation sessions: an observational study

Comparison of motion sensor and heart rate monitor for assessment of physical activity intensity in stroke outpatient rehabilitation sessions: an observational study

Ageing Suitability Evaluation of Residential Districts Based on Active Ageing Theory

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study

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