Sensor-based monitoring of sit-to-stand performance is indicative of objective and self-reported aspects of functional status in older adults

doi:10.1016/j.gaitpost.2015.03.350

Gait & Posture

Volume 41, Issue 4, May 2015, Pages 935-940

https://doi.org/10.1016/j.gaitpost.2015.03.350 Get rights and content

Highlights

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We investigated the clinical relevance of sensor-based sit-to-stand (STS) measures.
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In particular chest STS measures showed associations with standard clinical measures.
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Chest peak power and chest scaled peak power showed adequate discriminative ability.
•
Sensor-based monitoring of STS performance is clinically relevant in older adults.

Abstract

Studies show that body-fixed motion sensors can be used for long-term monitoring of sit-to-stand (STS) performance in older persons. However, it is unclear how sensor-based measures of STS performance relate to functional status in older adults. Therefore, this study investigated the associations between sensor-based STS measures and standard clinical measures of functional status in older adults. Participants (24 females, 12 males; 72–94 years) performed five normal STS movements while wearing motion sensors on the hip and chest. Objective measures were used to assess mobility (Timed-Up-and-Go Test, Five-Times-Sit-to-Stand Test, Stair Walk Test) and quadriceps strength. Self-reported questionnaires were used to assess limitations in activities of daily living (Groningen Activity Restriction Scale) and frailty (Groningen Frailty Indicator). In general, chest STS measures showed a larger number of significant associations and stronger associations with clinical measures than hip STS measures. Chest maximal velocity, chest peak power, chest scaled peak power and chest stabilization phase SD demonstrated significant associations (weak to strong) with all six clinical measures. Noteworthy is that hip stabilization phase SD showed significant associations (weak to moderate) with five clinical measures. In particular chest peak power and chest scaled peak power demonstrated a moderate ability to discriminate between higher and lower functioning individuals (area under the receiver–operating characteristic curve: 0.75–0.90). This study shows that in particular chest STS measures are indicative of objective and self-reported aspects of functional status in older adults. These findings support the clinical relevance of sensor-based monitoring of STS performance in older persons.

Introduction

With aging functional status may decline, therefore it is important to monitor functioning in older adults and to timely initiate interventions to prevent loss of functional abilities. Methods for the monitoring of motor functioning have been developed using body-fixed motion sensors [1]. Sensor-based measurement of leg power may be a relevant addition to existing sensor-based methods. Leg power is a determinant of mobility (changing basic body position, i.e. getting into and out of a body position and moving from one location to another [2]) and an important parameter for measuring intervention effects [3], [4], [5], [6]. Motion sensors can be used to estimate vertical peak power during the STS transfer [7] with adequate reliability and sensitivity to change [8], [9], [10].

However, it is unclear how sensor-based STS peak power and other STS measures (e.g. maximal velocity) relate to the functional status of older adults. Therefore, the aim of this study was to investigate the associations between sensor-based STS measures and standard clinical measures of functional status in older adults. STS measures were calculated from an individual sensor, because from a practical perspective a single sensor is preferred over multiple sensors. Studies show that leg power is associated with mobility, leg strength, self-reported measures of activities and mobility [3], [4], [5], [6]. Therefore, we hypothesized that sensor-based STS peak power is associated with mobility, leg strength, self-reported measures of limitations in activities and frailty. In addition, we hypothesized that STS peak power is more strongly associated with the aforementioned aspects of functional status than other STS measures. As part of the study aim, we also investigated the ability of STS peak power to discriminate between higher and lower functioning individuals.

Section snippets

Participants

Participants were 36 older adults (24 females, 12 males; age: 72–94 years (mean ± SD: 82.2 ± 5.4 years); mass: 48.0–104.4 kg (79.3 ± 14.1 kg); height: 1.46–1.89 m (1.66 ± 0.10 m)). Inclusion criteria were: Age≥70 years, being able to perform STS movements and walk ≥10 m (with or without a wheeled walker or cane). Recruitment took place in a health care center, residential care home and sheltered houses. Exclusion criteria were: lower extremity orthopedic surgery or a stroke within the six months before the

Results

Table 1 shows the measurement outcomes. As a result of physical limitations not all participants were able to perform all clinical measurements (Table 1). The hip sensor data of one participant, and the chest sensor data of two other participants, were not analyzed due to missing samples. Scaled peak power and maximal velocity demonstrated multicollinearity (r_s = 0.99) at both sensor locations.

Discussion

This study investigated the associations between sensor-based STS measures and standard clinical measures of functional status in older adults. In general, chest STS measures showed a larger number of significant associations and stronger associations with clinical measures than hip STS measures. Chest maximal velocity, chest peak power, chest scaled peak power and chest stabilization phase SD demonstrated significant associations (weak to strong) with all six clinical measures. Noteworthy is

Conflict of interest statement

All authors made substantial contributions to the conception and design of the study, data acquisition, data analysis, data interpretation, drafting the article or revising it critically for important intellectual content. Each of the authors has read and concurs with the content in the final manuscript. The authors have no conflicts of interest.

Acknowledgement

This study was supported by a grant from ZonMw (program ‘Diseasemanagement Chronische Ziekten’; project number 40-00812-98-09014). The sponsor was not involved in the study design, data collection, data analysis, data interpretation, writing of the manuscript and the decision to submit the manuscript for publication.

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Whether or not a predictive model can be developed by applying image recognition to analyze elderly individuals' posture during the sit-to-stand (STS) manoeuvre.
We enrolled sixty-six participants (24 males and 42 females) in an observational study design. To estimate posture key point information, we employed a region-based convolutional neural network model and utilized nine key points and their coordinates to calculate seven eigenvalues (X1-X7) that represented the motion curve features during the STS manoeuvre. One-way analysis of variance was performed to evaluate four STS strategies and four types of compensation strategies for three groups with different capacities (college students, community-dwelling elderly, and day care center elderly). Finally, a machine learning predictive model was established.
Significant differences (p < 0.05) were observed in all eigenvalues except X2 (momentum transfer phase, p = 0.168) between participant groups; significant differences (p < 0.05) were observed in all eigenvalues except X2 (p = 0.219) and X3 (hip-rising phase, p = 0.286) between STS patterns; significant differences (p < 0.05) were observed in all eigenvalues except X2 (p = 0.842) and X3 (p = 0.074) between compensation strategies. The motion curve eigenvalues of the seven posture key points were used to build a machine learning model with 85% accuracy in capacity detection, 70% accuracy in pattern detection, and 85% accuracy in compensation strategy detection.
This study preliminarily demonstrates that eigenvalues can be used to detect STS patterns and compensation strategies adopted by individuals with different capacities. Our machine learning model has excellent predictive accuracy and may be used to develop inexpensive and effective systems to help caregivers to continuously monitor STS patterns and compensation strategies of elderly individuals as warning signs of functional decline.
The Effect of Convergence Gamification Training in Community-Dwelling Older People: A Multicenter, Randomized Controlled Trial
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It is necessary to improve the health of older adults through exercise, but there is no concrete way to implement it or an environment in which they can exercise continuously. Our objective was to confirm the safety and efficacy of information technology (IT) convergence gamification exercise equipment for older adults. We tried to demonstrate equivalence to conventional exercise by comparing the functional improvement.
Randomized controlled trial, with 8-week-long IT convergence exercises 3 times a week vs conventional exercise.
40 community-dwelling participants aged 60-85 years.
Participants were randomly divided into a conventional exercise group (group 1) and an IT convergence exercise group (group 2). Both groups were trained for 8 weeks, and functional assessment was performed before training (pre-evaluation), after training, and after 4 weeks of rest.
There were functional improvements in both groups. A comparison of the differences in the functional assessment between pre-evaluation and after 8 weeks of training yielded the following results. In group 1, the mean Five Times Sit to Stand Test–30 seconds was scored as 3.60 ± 2.56 (P < .015); Five Times Sit to Stand Test–5 times, −1.75 ± 2.04 s (P < .015); Berg Balance Scale, 1.05 ± 1.39 (P < .015); Timed Up-and-Go test, −0.64 ± 0.64 s (P < .015); and 10-m Walking Test, −0.35 ± 0.47 s (P < .015). And in group 2, the mean Five Times Sit to Stand Test–30 seconds (s) was scored as 3.70 ± 2.62 (P < .015), Five Times Sit to Stand Test–5 times, −1.65 ± 1.59 s (P < .015); Berg Balance Scale, 1.05 ± 1.00 (P < .015); Timed Up-and-Go test, −0.93 ± 0.68 s (P < .015); 10-m Walking Test, −0.41 ± 0.489 s (P < .015); Chair Sit and Reach test, 2.23 ± 3.19 cm (P < .015); and Korean version of the Falls Efficacy Scale–International, −1.05 ± 1.43 (P < .015).
The results of this study suggest that the IT convergence gamification exercise equipment such as balpro110 has exercise effects similar to conventional exercise and also has advantages as an alternative to exercise for older adults in the next generation.
Effects of seat height on whole-body movement and lower limb muscle power during sit-to-stand movements in young and older individuals
2021, Journal of Biomechanics
Sit-to-stand (STS) movements from low seat height are not easily executed by older individuals. Although young individuals increase their lower limb muscle power (LLMP) based on the product of the ground reaction force (GRF) and center of mass velocity (CoMv) during STS movement from a low seat height, it remains unclear whether seat height has an effect on LLMP during STS movement in older individuals. The present study aimed to investigate differences in the LLMP during STS movements when seat height is lowered between young and older individuals. Twelve older and twelve height-matched young individuals were instructed to perform STS movements from low (20 cm), middle (40 cm), and high (60 cm) seat heights. STS movement and GRF were obtained by a motion analysis system and force plates. In the low-seat-height condition, the forward and upward LLMPs and the upward CoMv were significantly lower in older individuals than those in young individuals, but the forward CoMv was not. The completion time of STS movement from a low seat height was significantly longer in older individuals than in young individuals. Our findings suggest that the slower upward CoMv due to the lower upward LLMP extends the completion time of STS movement from a low seat height in older individuals. Furthermore, in the low-seat-height condition, older individuals may move their center of mass (CoM) forward in a different way when compared with young individuals, and they may not use forward LLMP for moving CoM forward.
Quaternion lifting scheme applied to the classification of motion data
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In this study, a new method of classification of skeleton-based motion data has been introduced. In the first stage, we performed multiscale feature extraction of rotational data. It is based on the proposed linear quaternion lifting scheme, with respect to the rotations coded by unit quaternions, which computes each scale based on the spherical linear interpolation (SLERP) prediction function and preserves the average signal value on each scale. Consequently, motion descriptors are extracted as quaternion attributes on different scales. The final recognition is performed by the nearest neighbor and minimum distance classifiers, adapted to support nonscalar features. Because of dimensionality of obtained descriptors, an attribute selection with respect to the multiresolution data has been proposed. It takes into consideration a specified number of resolutions, which is similar to low-pass filtering of the frequency domain. This method is utilized to solve the gait-based human identification problem. To validate such an application, a database containing data from 30 subjects was collected at the Human Motion Laboratory of the Polish-Japanese Academy of Information Technology (PJAIT). The obtained results were found to be satisfactory. In the best case, over 96% precision with only seven misclassified gaits of 178 samples was achieved.
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Citation Excerpt :
Standing-up and sitting-down are the most common and physically demanding manoeuvres that an individual performs [11–14], and the ability to stand up and sit down is a key factor in the maintenance of functional independence. Any change in the capability to perform these transitions in older individuals could be useful in determining the onset of frailty and provide an indicator of physical and cognitive impairment [12,13,15]. For those groups of people who have mobility related conditions, such as a stroke, the recovery of the ability to stand up and sit down is crucial and quantification of the quality of these movements could be useful for monitoring progress of recovery.
Standing up, sitting down and walking require considerable effort and coordination, which are crucial indicators to rehabilitation (e.g. stroke), and in older populations may indicate the onset of frailty and physical and cognitive decline. Currently, there are few reports robustly quantifying sit-to-stand and stand-to-sit transitions in free-living environments. The aim of this study was to identify and quantify these transitions using the peak velocity of sit-to-stand and stand-to-sit transitions to determine if these velocities were different in a healthy cohort and a mobility-impaired population.
Free-living sit-to-stand and stand-to-sit acceleration data were recorded from 21 healthy volunteers and 34 stroke survivors using activPAL3™ monitors over a one-week period. Thigh inclination velocity was calculated from these accelerometer data. Maximum velocities were compared between populations.
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There were significant differences in the mean peak velocity of sit-to-stand and stand-to-sit transitions between the groups. Variation in an individual's mean peak velocity may be associated with the ability to perform these transitions. This method could be used to evaluate the effectiveness of interventions following injury such as stroke, as well as monitor decline in functional ability.
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As the aging and cancer populations in the world continue to increase, the need for complements to traditional geriatric assessments and the logical incorporation of fast and reliable telehealth tools have become interlinked. In the United States, studies examining the use of telehealth for chronic disease management have shown promising results in small groups. The implementation of health technology on a broader scale requires older adults to both accept and adapt such innovation into routine medical care. Though the commercial and recreational use of new technology has increased in older individuals, the transition into creating a smart and connected home that can interface with both patients and healthcare professionals is in its early phases. Current limitations include an inherent digital divide, as well as concerns regarding privacy, data volume, rapid change, cost and reimbursement. The emergence of low-cost, high-fidelity wearable sensors with a spectrum of clinical utility may be the key to increased use and adaptation by older adults. An opportunity to utilize wearable sensors for objective and real-time assessment of older patients with cancer for baseline functional status and treatment toxicity may be on the horizon.

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Sensor-based monitoring of sit-to-stand performance is indicative of objective and self-reported aspects of functional status in older adults

Highlights

Abstract

Introduction

Section snippets

Participants

Results

Discussion

Conflict of interest statement

Acknowledgement

Gait Posture

Gait Posture

Gait Posture

Gait Posture

Soc Sci Med

J Am Med Dir Assoc

Prev Vet Med

Med Eng Phys

Mobility assessment in older people: new possibilities and challenges

Eur J Ageing

International classification of functioning, disability and health: ICF. Detailed classification with definitions, activities and participation

A comparison of leg power and leg strength within the InCHIANTI study: which influences mobility more

J Gerontol A Biol Sci Med Sci

Strength, power and related functional ability of healthy people aged 65–89 years

Age Ageing

Association of muscle power with functional status in community-dwelling elderly women

J Gerontol A Biol Sci Med Sci

Relationship between strength, power and balance performance in seniors

Gerontology

Test–retest reliability of a pendant-worn sensor device in measuring chair rise performance in older persons

Sensors (Basel)