Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ranging (2D-LiDAR) technology. Using an object-tracking algorithm, we conducted a validation study of the spatiotemporal tracking of ankle locations of young, healthy participants (n = 4) by comparing our tool and a stereo camera with the motion capture system as a gold standard modality. We also assessed parameters including step length, step width, cadence, and gait speed. The 2D-LiDAR system showed a much better accuracy than that of a stereo camera system, where mean absolute errors were 46.2 ± 17.8 mm and 116.3 ± 69.6 mm, respectively. Gait parameters from the 2D-LiDAR system were in good agreement with those from the motion capture system (r = 0.955 for step length, r = 0.911 for cadence). Simultaneous tracking of multiple targets by the 2D-LiDAR system was also demonstrated. The novel system might be useful in space and resource constrained clinical practice for older adults.

Purpose The importance of evaluating frailty status of older adults in clinical practice has been gaining attention with cumulative evidence showing its relevance in clinical outcomes and decision-making. We aimed to develop and validate whether the functional age predicted by an electronic continuous short physical performance battery (eSPPB) could predict frailty status. Patients and Methods We reviewed medical records of outpatients (N=834) of Asan Medical Center, aged 51–95 years. We used the eSPPB data of 717 patients as a development cohort, and that of 117 patients, who also underwent comprehensive geriatric assessments, as a validation cohort. Frailty index was calculated by counting deficits of 45 geriatric items including comorbidities, daily functions, mobility, mood, and cognition. For functional age, we used balance score (0–4), gait speed (m/s), and stand-up time (s) measured 5 times in the chair rise test. Results From the development cohort, we established a functional age using the formula (83.61 − 1.98*[balance score] − 5.21*[gait speed] + 0.23*[stand-up time]), by multivariate linear regression analysis with chronological age as a dependent variable (R 2 = 0.233). In the validation cohort, the functional age positively correlated with frailty index (p < 0.001). C-statistics classifying frailty (defined as frailty index ≥0.25) was higher (p < 0.001) with functional age (0.912) than that with chronological age (0.637). A cut-off functional age of ≥77.2 years maximized Youden’s J when screening for frailty, with sensitivity of 94.4% and specificity of 80.8%. Conclusion A newly developed functional age predictor using eSPPB parameters can predict the frailty status as defined by the deficit accumulation method and may serve as a physical biomarker of human aging.

Accumulating evidence suggests the clinical importance of assessing the physical performance of the lower extremities in older adults as a diagnostic marker, 1-3) outcome predictor, [4][5][6] and clinical outcome measure. [7][8][9] For example, the assessment of the physical performance of the lower extremities is an essential component in diagnosing sarcopenia, a common geriatric syndrome defined as a state of decreased muscle mass, muscle strength, and/or physical performance. 2,10) Longitudinal studies have shown that decreased physical performance of the lower extremities is associated with falls, functional decline, and mortality. [11][12][13][14][15] Furthermore, meaning-

Background: The Short Physical Performance Battery (SPPB) is a widely accepted test for measuring lower extremity function in older adults. However, there are concerns regarding the examination time required to conduct a complete SPPB consisting of three components (walking speed, chair rise, and standing balance tests) in clinical settings. We aimed to assess specific examination times for each component of the electronic Short Physical Performance Battery (eSPPB) and compare the ability of the original three-component examinations (eSPPB) and a faster, two-component examination without a balance test (electronic Quick Physical Performance Battery, eQPPB) to classify sarcopenia. Methods: The study was a retrospective, cross-sectional study which included 124 ambulatory outpatients who underwent physical performance examination at a geriatric clinic of a tertiary, academic hospital in Seoul, Korea, between December 2020 and March 2021. For eSPPB, we used a toolkit containing sensors and software (Dyphi, Daejeon, Korea) developed to measure standing balance, walking speed, and chair rise test results. Component-specific time stamps were used to log the raw data. Duration of balance examination, 5 times sit-to-stand test (5XSST), and walking speed examination were calculated. Sarcopenia was determined using the 2019 Asian Working Group for Sarcopenia (AWGS) guideline. Results: The median age was 78 years (interquartile range, IQR: 73,82) and 77 subjects (62.1%) were female. The total mean eSPPB test time was 124.8 ± 29.0 s (balance test time 61.8 ± 12.3 s, 49.5%; gait speed test time 34.3 ± 11.9 s, 27.5%; and 5XSST time 28.7 ± 19.1 s, 23.0%). The total mean eQPPB test time was 63.0 ± 25.4 s. Based on the AWGS criteria, 34 (27.4%) patient’s results were consistent with sarcopenia. C-statistics for classifying sarcopenia were 0.83 for eSPPB and 0.85 for eQPPB (p = 0.264), while eQPPB took 49.5% less measurement time compared with eSPPB. Conclusion: Breakdowns of eSPPB test times were identified. Omitting balance tests may reduce test time without significantly affecting the classifying ability of eSPPB for sarcopenia.

Acquiring gait parameters from usual walking is important to predict clinical outcomes, including life expectancy, risk of fall, and neurocognitive performance, in older people. For comprehensive gait analysis, instruments such as marker-based motion analysis systems and walkways with pressure sensor arrays are necessary. Traditional instruments are bulky, complex, expensive, and intrinsically intrusive. Requirements of dedicated spaces for installation and specialized staff make it difficult to utilize traditional gait analysis instruments in most outpatient clinics. We present a novel gait analysis tool that is small, highly accurate, easy-to-use, and non-intrusive and is based on two-dimensional light detection and ranging technology. Using an object-tracking algorithm, we conducted a validation study of spatiotemporal tracking of ankle locations of subjects by comparing our tool with a gold standard modality. Our tool showed successful acquisition of gait parameters from usual walking motions and trackability with multiple targets in noisy conditions, including typical clinical environments.