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Introduction: An early detection of impaired functional performance is critical to enhance symptom management for patients with chronic obstructive pulmonary disease (COPD). However, conventional functional measures based on walking assessments are often impractical for small clinics where the available space to administrate gait-based test is limited. This study examined the feasibility and effectiveness of an upper-extremity frailty meter (FM) in identifying digital measures of functional performance and assessing frailty in COPD patients.Methods: Forty-eight patients with COPD (age = 68.8 ± 8.5 years, body mass index [BMI] = 28.7 ± 5.8 kg/m2) and 49 controls (age = 70.0 ± 3.0 years, BMI = 28.7 ± 6.1 kg/m2) were recruited. All participants performed a 20-s repetitive elbow flexion-extension test using a wrist-worn FM sensor. Functional performance was quantified by FM metrics, including speed (slowness), range of motion (rigidity), power (weakness), flexion and extension time (slowness), as well as speed and power reduction (exhaustion). Conventional functional measures, including timed-up-and-go test, gait and balance tests, and 5 repetition sit-to-stand test, were also performed.Results: Compared to controls, COPD patients exhibited deteriorated performances in all conventional functional assessments (d = 0.64-1.26, p < 0.010) and all FM metrics (d = 0.45-1.54, p < 0.050). FM metrics had significant agreements with conventional assessment tools (|r| = 0.35-0.55, p ≤ 0.001). FM metrics efficiently identified COPD patients with pre-frailty and frailty (d = 0.82-2.12, p < 0.050).Conclusion: This study proposes the feasibility of using a 20-s repetitive elbow flexion-extension test and wrist-worn sensor-derived frailty metrics as an alternative and practical solution to evaluate functional performance in COPD patients. Its simplicity and low risk for test administration may also facilitate its application for remote patient monitoring. Furthermore, in settings where the administration of walking test is impractical, for example, when ventilator support is needed or space is limited, FM may be used as an alternative solution. Future studies are encouraged to use the FM to quantitatively monitor the progressive decline in functional performance and quantify outcomes of rehabilitation interventions. [ABSTRACT FROM AUTHOR]

Background: Cognitive frailty (CF), defined as the simultaneous presence of cognitive impairment and physical frailty, is a clinical symptom in early-stage dementia with promise in assessing the risk of dementia. The purpose of this study was to use wearables to determine the most sensitive digital gait biomarkers to identify CF. Methods: Of 121 older adults (age = 78.9 ± 8.2 years, body mass index = 26.6 ± 5.5 kg/m2) who were evaluated with a comprehensive neurological exam and the Fried frailty criteria, 41 participants (34%) were identified with CF and 80 participants (66%) were identified without CF. Gait performance of participants was assessed under single task (walking without cognitive distraction) and dual task (walking while counting backward from a random number) using a validated wearable platform. Participants walked at habitual speed over a distance of 10 m. A validated algorithm was used to determine steady-state walking. Gait parameters of interest include steady-state gait speed, stride length, gait cycle time, double support, and gait unsteadiness. In addition, speed and stride length were normalized by height. Results: Our results suggest that compared to the group without CF, the CF group had deteriorated gait performances in both single-task and dual-task walking (Cohen's effect size d = 0.42–0.97, p < 0.050). The largest effect size was observed in normalized dual-task gait speed (d = 0.97, p < 0.001). The use of dual-task gait speed improved the area under the curve (AUC) to distinguish CF cases to 0.76 from 0.73 observed for the single-task gait speed. Adding both single-task and dual-task gait speeds did not noticeably change AUC. However, when additional gait parameters such as gait unsteadiness, stride length, and double support were included in the model, AUC was improved to 0.87. Conclusions: This study suggests that gait performances measured by wearable sensors are potential digital biomarkers of CF among older adults. Dual-task gait and other detailed gait metrics provide value for identifying CF above gait speed alone. Future studies need to examine the potential benefits of gait performances for early diagnosis of CF and/or tracking its severity over time. [ABSTRACT FROM AUTHOR]

Introduction: Parkinson's disease (PD) progressively impairs motor and cognitive performance. The current tools to detect decline in motor and cognitive functioning are often impractical for busy clinics and home settings. To address the gap, we designed an instrumented trail-making task (iTMT) based on a wearable sensor (worn on the shin) with interactive game-based software installed on a tablet. The iTMT test includes reaching to 5 indexed circles, a combination of numbers (1–3) and letters (A&B) randomly positioned inside target circles, in a sequential order, which virtually appears on a screen kept in front of the participants, by rotating one's ankle joint while standing and holding a chair for safety. By measuring time to complete iTMT task (iTMT time), iTMT enables quantifying cognitive-motor performance. Purpose: This study's objective is to examine the feasibility of iTMT to detect early cognitive-motor decline in PDs. Method: Three groups of volunteers, including 14 cognitively normal (CN) older adults, 14 PDs, and 11 mild cognitive impaireds (MCI), were recruited. Participants completed MoCA, 20 m walking test, and 3 trials of iTMT. Results: All participants enabled to complete iTMT with <3 min, indicating high feasibility. The average iTMT time for CN-Older, PD, and MCI participants were 20.9 ± 0.9 s, 32.3 ± 2.4 s, and 40.9 ± 4.5 s, respectively. After adjusting for age and education level, pairwise comparison suggested large effect sizes for iTMT between CN-older versus PD (Cohen's d = 1.7, p = 0.024) and CN-older versus MCI (d = 1.57, p < 0.01). Significant correlations were observed when comparing iTMT time with the gait speed (r = −0.4, p = 0.011) and MoCA score (r = −0.56, p < 0.01). Conclusion: This study demonstrated the feasibility and early results supporting the potential application of iTMT to determine cognitive-motor and distinguishing individuals with MCI and PD from CN-older adults. Future studies are warranted to test the ability of iTMT to track its subtle changes over time. [ABSTRACT FROM AUTHOR]

Background: The physical frailty assessment tools that are currently available are often time consuming to use with limited feasibility.Objective: To address these limitations, an instrumented trail-making task (iTMT) platform was developed using wearable technology to automate quantification of frailty phenotypes without the need of a frailty walking test.Methods: Sixty-one older adults (age = 72.8 ± 9.9 years, body mass index [BMI] = 27.4 ± 4.9 kg/m2) were recruited. According to the Fried Frailty Criteria, 39% of participants were determined as robust and 61% as non-robust (pre-frail or frail). In addition, 17 young subjects (age = 29.0 ± 7.2 years, BMI = 26.2 ± 4.6 kg/m2) were recruited to determine the healthy benchmark. The iTMT included reaching 5 indexed circles (including numbers 1-to-3 and letters A&B placed in random orders), which virtually appeared on a computer-screen, by rotating one's ankle-joint while standing. By using an ankle-worn inertial sensor, 3D ankle-rotation was estimated and mapped into navigation of a computer-cursor in real-time (100 Hz), allowing subjects to navigate the computer-cursor to perform the iTMT. The ankle-sensor was also used for quantifying ankle-rotation velocity (representing slowness), its decline during the test (representing exhaustion), and ankle-velocity variability (representing movement inefficiency), as well as the power (representing weakness) generated during the test. Comparative assessments included Fried frailty phenotypes and gait assessment.Results: All subjects were able to complete the iTMT, with an average completion time of 125 ± 85 s. The iTMT-derived parameters were able to identify the presence and absence of slowness, exhaustion, weakness, and inactivity phenotypes (Cohen's d effect size = 0.90-1.40). The iTMT Velocity was significantly different between groups (d = 0.62-1.47). Significant correlation was observed between the iTMT Velocity and gait speed (r = 0.684 p < 0.001). The iTMT-derived parameters and age together enabled significant distinguishing of non-robust cases with area under curve of 0.834, sensitivity of 83%, and specificity of 67%.Conclusion: This study demonstrated a non-gait-based wearable platform to objectively quantify frailty phenotypes and determine physical frailty, using a quick and practical test. This platform may address the hurdles of conventional physical frailty phenotypes methods by replacing the conventional frailty walking test with an automated and objective process that reduces the time of assessment and is more practical for those with mobility limitations. [ABSTRACT FROM AUTHOR]

Background: Objective and time-effective tools are needed to identify motor-cognitive impairment and facilitate early intervention.Objective: We examined the feasibility, accuracy, and reliability of an instrumented trail-making task (iTMT) using a wearable sensor to identify motor-cognitive impairment among older adults.Methods: Thirty subjects (age = 82.2 + 6.1 years, body mass index = 25.7 + 4.8, female = 43.3%) in 3 age-matched groups, 11 healthy, 10 with amnestic mild cognitive impairment (aMCI), and 9 with Alzheimer disease (AD), were recruited. Subjects completed iTMT, using a wearable sensor attached to the leg, which translates the motion of the ankle into a human-machine interface. iTMT tests included reaching to 5 indexed circles on a computer screen by moving the ankle-joint while standing. iTMT was quantified by the time required to reach all circles in the correct sequence. Three iTMT tests were designed, including numbers (1-5) positioned in a fixed (iTMTfixed) or random (iTMTrandom) order, or numbers (1-3) and letters (A and B) positioned in random order (iTMTnumber-letter). Each test was repeated twice to examine test-retest reliability. In addition, the conventional trail-making task (TMT A and B), Montreal Cognitive Assessment (MoCA), and dual-task cost (DTC: gait-speed difference between walking alone and walking while counting backward) were used as references. Re sults: Good-to-excellent reliability was achieved for all iTMT tests (intraclass correlation [ICC] = 0.742-0.836). Between-group difference was more pronounced, when using iTMTnumber-letter, with average completion time of 26.3 ± 12.4, 37.8 ± 14.1, and 61.8 ± 34.1 s, respectively, for healthy, aMCI, and AD groups (p = 0.006). Pairwise comparison suggested strong effect sizes between AD and healthy (Cohen's d = 1.384, p = 0.001) and between aMCI and AD (d = 0.923, p = 0.028). Significant correlation was observed when comparing iTMTnumber-letter with MoCA (r = -0.598, p = 0.001), TMT A (r = 0.519, p = 0.006), TMT B (r = 0.666, p < 0.001), and DTC (r = 0.713, p < 0.001).Conclusion: This study demonstrated proof of concept of a simple, safe, and practical iTMT system with promising results to identify cognitive and dual-task ability impairment among older adults, including those with aMCI and AD. Future studies need to confirm these observations in larger samples, as well as iTMT's ability to track motor-cognitive decline over time. [ABSTRACT FROM AUTHOR]