Assessing the role of ankle and hip joint proprioceptive information in balance recovery using vibratory stimulation.

Background: Previous work suggests that proprioceptive information from ankle and hip are crucial in maintaining balance during upright standing; however, the contribution of these proprioceptive information during stepping balance recovery in not clear. The goal of the current study was to assess the role of ankle and hip proprioceptive information on balance recovery performance by manipulating type 1a afferent in muscle spindles using vibratory stimulation. Methods: Twenty healthy young participants were recruited (age = 22.2 ± 2.7 years) and were randomly assigned to balance recovery sessions with either ankle or hip stimulation. Trip-like perturbations were imposed using a modified treadmill setup with a protecting harness. Vibratory stimulation was imposed bilaterally on ankle and hip muscles to expose participants to three condition of no-vibration, 40Hz vibration, and 80Hz vibration. Kinematics of the trunk and lower-extremities were measured using wearable sensors to characterize balance recovery performance. Outcomes were response time, recovery step length, trunk angle during toe-off and heel-strike of recovery stepping, and required time for full recovery. Findings: Ankle vibratory stimulation elicited main effects on reaction time and recovery step length (p < 0.002); reaction time and recovery step length increased by 23.0% and 21.2%, respectively, on average across the conditions. Hip vibratory stimulation elicited significant increase in the full recovery time (p = 0.019), with 55.3% increase on average across the conditions. Interpretation: Current findings provided evidence that vibratory stimulation can affect the balance recovery performance, causing a delayed recovery initiation and an impaired balance refinement after the recovery stepping when applied to ankle and hip muscles, respectively.

Hyper-acute effects of sub-concussive soccer headers on brain function and hemodynamics.

Introduction: Sub-concussive head impacts in soccer are drawing increasing research attention regarding their acute and long-term effects as players may experience thousands of headers in a single season. During these impacts, the head experiences rapid acceleration similar to what occurs during a concussion, but without the clinical implications. The physical mechanism and response to repetitive impacts are not completely understood. The objective of this work was to examine the immediate functional outcomes of sub-concussive level impacts from soccer heading in a natural, non-laboratory environment. Methods: Twenty university level soccer athletes were instrumented with sensor-mounted bite bars to record impacts from 10 consecutive soccer headers. Pre- and post-header measurements were collected to determine hyper-acute changes, i.e., within minutes after exposure. This included measuring blood flow velocity using transcranial Doppler (TCD) ultrasound, oxyhemoglobin concentration using functional near infrared spectroscopy imaging (fNIRS), and upper extremity dual-task (UEF) neurocognitive testing. Results: On average, the athletes experienced 30.7 ± 8.9 g peak linear acceleration and 7.2 ± 3.1 rad/s peak angular velocity, respectively. Results from fNIRS measurements showed an increase in the brain oxygenation for the left prefrontal cortex (PC) (p = 0.002), and the left motor cortex (MC) (p = 0.007) following the soccer headers. Additional analysis of the fNIRS time series demonstrates increased sample entropy of the signal after the headers in the right PC (p = 0.02), right MC (p = 0.004), and left MC (p = 0.04). Discussion: These combined results reveal some variations in brain oxygenation immediately detected after repetitive headers. Significant changes in balance and neurocognitive function were not observed in this study, indicating a mild level of head impacts. This is the first study to observe hemodynamic changes immediately after sub-concussive impacts using non-invasive portable imaging technology. In combination with head kinematic measurements, this information can give new insights and a framework for immediate monitoring of sub-concussive impacts on the head.

Sensor-Based Assessment of Variability in Daily Physical Activity and Frailty.

INTRODUCTION: Frailty is a common geriatric syndrome associated with decline in physiological reserve. While several digital biomarkers of daily physical activity (DPA) have been used in frailty assessment, the association between DPA variability and frailty is still not clear. The goal of this study was to determine the association between frailty and DPA variability. METHODS: This is an observational cross-sectional study conducted between September 2012 and November 2013. Older adults (≥65 years), without any severe mobility disorder, and the ability to walk 10 m (with or without an assistive device) were eligible for the study. DPA including sitting, standing, walking, lying, and postural transition were recorded for 48 h continuously. DPA variability was analyzed from two perspectives: (i) DPA duration variability in terms of coefficient of variation (CoV) of sitting, standing, walking, and lying down durations; and (ii) DPA performance variability in terms of CoV of sit-to-stand (SiSt) and stand-to-sit (StSi) durations and stride time (i.e., slope of power spectral density - PSD). RESULTS: Data was analyzed from 126 participants (44 non-frail, 60 pre-frail, and 22 frail). For DPA duration variability, CoV of lying and walking duration was significantly larger among non-frail compared to pre-frail and frail groups (p < 0.03, d = 0.89 ± 0.40). For DPA performance variability, StSi CoV and PSD slope were significantly smaller for non-frail compared to pre-frail and frail groups (p < 0.05, d = 0.78 ± 0.19). CONCLUSION: Lower DPA duration variability in pre-frail and frail groups may be attributed to the set daily routines frail older adults tend to follow, compared to variable physical activity routines of non-frail older adults. Higher DPA performance variability in the frail group may be attributed to reduced physiological capabilities toward walking for longer durations and the reduced muscle strength in the lower extremities, leading to incosistency in performing postural transitions.

Association between dual-task function and neuropsychological testing in older adults with cognitive impairment.

INTRODUCTION: Despite the current high prevalence of dementia, more than half of older adult patients never receive an evaluation. Current evaluation methods are lengthy, cumbersome, and not viable for busy clinics. This indicates that, despite recent improvements, a quick and objective routine test for screening cognitive decline in older adults is still needed. Poor dual-task gait performance has been previously associated with decreased executive and neuropsychological function. However, gait tests are not always viable for clinics or older patients. METHODS: The aim of this study was to assess the relationship between a novel upper-extremity function (UEF) dual-task performance and neuropsychological test results in older adults. For UEF dual-tasks, participants performed a consistent elbow flexion and extension, while counting backwards in increments of threes or ones. Wearable motion sensors were attached to the forearm and upper-arm to measure accuracy and speed of elbow flexion kinematics to calculate a UEF cognitive score. RESULTS: We recruited older adults at three stages: cognitively normal (CN) (n = 35), mild cognitively impaired (MCI) of the Alzheimer's type (n = 34), and Alzheimer's disease (AD) (n = 22). The results demonstrate significant correlations between UEF cognitive score and mini-mental state examination (MMSE), Mini-Cog, Category fluency, Benson complex figure copy, Trail making test, and Montreal cognitive assessment (MOCA) (r values between -0.2355 and -0.6037 and p < 0.0288). DISCUSSION: UEF dual-task was associated with executive function, orientation, repetition, abstraction, verbal recall, attention and calculation, language and visual construction. Of the associated brain domains, UEF dual-task was most significantly associated with executive function, visual construction, and delayed recall. The results from this study convey potential for UEF dual-task as a safe and convenient cognitive impairment screening method.

Associating Frailty and Dynamic Dysregulation between Motor and Cardiac Autonomic Systems.

Frailty is a geriatric syndrome associated with the lack of physiological reserve and consequent adverse outcomes (therapy complications and death) in older adults. Recent research has shown associations between heart rate (HR) dynamics (HR changes during physical activity) with frailty. The goal of the present study was to determine the effect of frailty on the interconnection between motor and cardiac systems during a localized upper-extremity function (UEF) test. Fifty-six older adults aged 65 or older were recruited and performed the UEF task of rapid elbow flexion for 20-seconds with the right arm. Frailty was assessed using the Fried phenotype. Wearable gyroscopes and electrocardiography were used to measure motor function and HR dynamics. Using convergent cross-mapping (CCM) the interconnection between motor (angular displacement) and cardiac (HR) performance was assessed. A significantly weaker interconnection was observed among pre-frail and frail participants compared to non-frail individuals (p<0.01, effect size=0.81±0.08). Using logistic models pre-frailty and frailty were identified with sensitivity and specificity of 82% to 89%, using motor, HR dynamics, and interconnection parameters. Findings suggested a strong association between cardiac-motor interconnection and frailty. Adding CCM parameters in a multimodal model may provide a promising measure of frailty.

A computational musculoskeletal arm model for assessing muscle dysfunction in chronic obstructive pulmonary disease.

Computational models have been used extensively to assess diseases and disabilities effects on musculoskeletal system dysfunction. In the current study, we developed a two degree-of-freedom subject-specific second-order task-specific arm model for characterizing upper-extremity function (UEF) to assess muscle dysfunction due to chronic obstructive pulmonary disease (COPD). Older adults (65 years or older) with and without COPD and healthy young control participants (18 to 30 years) were recruited. First, we evaluated the musculoskeletal arm model using electromyography (EMG) data. Second, we compared the computational musculoskeletal arm model parameters along with EMG-based time lag and kinematics parameters (such as elbow angular velocity) between participants. The developed model showed strong cross-correlation with EMG data for biceps (0.905, 0.915) and moderate cross-correlation for triceps (0.717, 0.672) within both fast and normal pace tasks among older adults with COPD. We also showed that parameters obtained from the musculoskeletal model were significantly different between COPD and healthy participants. On average, higher effect sizes were achieved for parameters obtained from the musculoskeletal model, especially for co-contraction measures (effect size = 1.650 ± 0.606, p < 0.001), which was the only parameter that showed significant differences between all pairwise comparisons across the three groups. These findings suggest that studying the muscle performance and co-contraction, may provide better information regarding neuromuscular deficiencies compared to kinematics data. The presented model has potential for assessing functional capacity and studying longitudinal outcomes in COPD.

Neuroimaging, wearable sensors, and blood-based biomarkers reveal hyperacute changes in the brain after sub-concussive impacts.

Impacts in mixed martial arts (MMA) have been studied mainly in regard to the long-term effects of concussions. However, repetitive sub-concussive head impacts at the hyperacute phase (minutes after impact), are not understood. The head experiences rapid acceleration similar to a concussion, but without clinical symptoms. We utilize portable neuroimaging technology - transcranial Doppler (TCD) ultrasound and functional near infrared spectroscopy (fNIRS) - to estimate the extent of pre- and post-differences following contact and non-contact sparring sessions in nine MMA athletes. In addition, the extent of changes in neurofilament light (NfL) protein biomarker concentrations, and neurocognitive/balance parameters were determined following impacts. Athletes were instrumented with sensor-based mouth guards to record head kinematics. TCD and fNIRS results demonstrated significantly increased blood flow velocity (p = 0.01) as well as prefrontal (p = 0.01) and motor cortex (p = 0.04) oxygenation, only following the contact sparring sessions. This increase after contact was correlated with the cumulative angular acceleration experienced during impacts (p = 0.01). In addition, the NfL biomarker demonstrated positive correlations with angular acceleration (p = 0.03), and maximum principal and fiber strain (p = 0.01). On average athletes experienced 23.9 ± 2.9 g peak linear acceleration, 10.29 ± 1.1 rad/s peak angular velocity, and 1,502.3 ± 532.3 rad/s2 angular acceleration. Balance parameters were significantly increased following contact sparring for medial-lateral (ML) center of mass (COM) sway, and ML ankle angle (p = 0.01), illustrating worsened balance. These combined results reveal significant changes in brain hemodynamics and neurophysiological parameters that occur immediately after sub-concussive impacts and suggest that the physical impact to the head plays an important role in these changes.

Brain function complexity during dual-tasking is associated with cognitive impairment and age.

BACKGROUND AND PURPOSE: Early diagnosis of cognitive impairment is important because symptoms can be delayed through therapies. Synaptic disconnections are the key characteristics of dementia, and through nonlinear complexity analysis of brain function, it is possible to identify long-range synaptic disconnections in the brain. METHODS: We investigated the capability of a novel upper-extremity function (UEF) dual-task paradigm in the functional MRI (fMRI) setting, where the participant flexes and extends their arm while counting, to differentiate between cognitively normal (CN) and those with mild cognitive impairment (MCI). We used multiscale entropy (MSE) complexity analysis of the blood oxygen-level dependent time-series across neural networks and brain regions. Outside of the fMRI, we used the UEF dual-task test, while the elbow kinematics were measured using motion sensors, to record the motor function score. RESULTS: Results showed 34% lower MSE values in MCI compared to CN (p<.04 for all regions and networks except cerebellum when counting down by one; effect size = 1.35±0.15) and a negative correlation between MSE values and age (average r2 of 0.30 for counting down by one and 0.36 for counting backward by three). Results also showed an improvement in the logistic regression model sensitivity by 14-24% in predicting the presence of MCI when brain function measure was added to the motor function score (kinematics data). CONCLUSIONS: Current findings suggest that combining measures of neural network and motor function, in addition to neuropsychological testing, may provide an accurate tool for assessing early-stage cognitive impairment and age-related decline in cognition.

Novel imaging markers for altered cerebrovascular morphology in aging, stroke, and Alzheimer's disease.

BACKGROUND AND PURPOSE: Altered brain vasculature is a key phenomenon in several neurologic disorders. This paper presents a quantitative assessment of the anatomical variations in the Circle of Willis (CoW) and vascular morphology in healthy aging, acute ischemic stroke (AIS) and Alzheimer's Disease (AD). METHODS: We used our novel automatic method to segment and extract geometric features of the cerebral vasculature from MR angiography scans of 175 healthy subjects, which were used to create a probabilistic atlas of cerebrovasculature and to study normal aging and intersubject variations in CoW anatomy. Subsequently, we quantified and analyzed vascular alterations in 45AIS and 50 AD patients, two prominent cerebrovascular and neurodegenerative disorders. RESULTS: In the sampled cohort, we determined that the CoW is fully formed in only 35% of healthy adults and found significantly (p < .05) increased tortuosity and fractality, with increasing age and also with disease in both AIS and AD. We also found significantly lower vessel length, volume, and number of branches in AIS patients, as expected. The AD cerebral vessels exhibited significantly smaller diameter and more complex branching patterns, compared to age-matched healthy adults. These changes were significantly heightened (p < .05) among healthy, early onset mild AD, and moderate/severe dementia groups. CONCLUSION: Although our study does not include longitudinal data due to paucity of such datasets, the specific geometric features and quantitative comparisons demonstrate the potential for using vascular morphology as a noninvasive imaging biomarker for neurologic disorders.

Frailty assessment using a novel approach based on combined motor and cardiac functions: a pilot study.

BACKGROUND: Previous research showed association between frailty and an impaired autonomic nervous system; however, the direct effect of frailty on heart rate (HR) behavior during physical activity is unclear. The purpose of the current study was to determine the association between HR increase and decrease with frailty during a localized upper-extremity function (UEF) task to establish a multimodal frailty test. METHODS: Older adults aged 65 or older were recruited and performed the UEF task of rapid elbow flexion for 20 s with the right arm. Wearable gyroscopes were used to measure forearm and upper-arm motion, and electrocardiography were recorded using leads on the left chest. Using this setup, HR dynamics were measured, including time to peak HR, recovery time, percentage increase in HR during UEF, and percentage decrease in HR during recovery after UEF. RESULTS: Fifty-six eligible participants were recruited, including 12 non-frail (age = 76.92 ± 7.32 years), and 40 pre-frail (age = 80.53 ± 8.12 years), and four frail individuals (age = 88.25 ± 4.43 years). Analysis of variance models showed that the percentage increase in HR during UEF and percentage decrease in HR during recovery were both 47% smaller in pre-frail/frail older adults compared to non-frails (p < 0.01, effect size = 0.70 and 0.62 for increase and decrease percentages). Using logistic models with both UEF kinematics and HR parameters as independent variables, frailty was predicted with a sensitivity of 0.82 and specificity of 0.83. CONCLUSION: Current findings showed evidence of strong association between HR dynamics and frailty. It is suggested that combining kinematics and HR data in a multimodal model may provide a promising objective tool for frailty assessment.

The association between heart rate behavior and gait performance: The moderating effect of frailty.

INTRODUCTION: Research suggests that frailty not only influence individual systems, but also it affects the interconnection between them. However, no study exists to show how the interplay between cardiovascular and motor performance is compromised with frailty. AIM: To investigate the effect of frailty on the association between heart rate (HR) dynamics and gait performance. METHODS: Eighty-five older adults (≥65 years and able to walk 9.14 meters) were recruited (October 2016-March 2018) and categorized into 26 non-frail (age = 78.65±7.46 years) and 59 pre-frail/frail individuals (age = 81.01±8.17) based on the Fried frailty phenotype. Participants performed gait tasks while equipped with a wearable electrocardiogram (ECG) sensor attached to the chest, as well as wearable gyroscopes for gait assessment. HR dynamic parameters were extracted, including time to peak HR and percentage increase in HR in response to walking. Using the gyroscope sensors gait parameters were recorded including stride length, stride velocity, mean swing velocity, and double support. RESULTS: Among the pre-frail/frail group, time to peak HR was significantly correlated with all gait parameters (p<0.0001, r = 0.51-0.59); however, for the non-frail group, none of the correlations between HR dynamics and gait performance parameters were significant (p>0.45, r = 0.03-0.15). The moderation analysis of time to peak HR, demonstrated a significant interaction effect of HR dynamics and frailty status on walking velocity (p<0.01), and the interaction effect was marginally non-significant for other gait parameters (p>0.10). CONCLUSIONS: Current findings, for the first time, suggest that a compromised motor and cardiac autonomic interaction exist among pre-frail/frail older adults; an impaired HR performance (i.e., slower increase of HR in response to stressors) may lead to a slower walking performance. Assessing physical performance and its corresponding HR behavior should be studied as a tool for frailty screening and providing insights about the underlying cardiovascular-related mechanism leading to physical frailty.

Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach.

Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on resting state heart rate characteristics or heart rate monitoring without controlling for physical activities, the objective of the current study was to classify pre-frail/frail vs non-frail older adults using heart rate response to physical activity (heart rate dynamics). Eighty-eight older adults (≥65 years) were recruited and stratified into frailty groups based on the five-component Fried frailty phenotype. Groups consisted of 27 non-frail (age = 78.80±7.23) and 61 pre-frail/frail (age = 80.63±8.07) individuals. Participants performed a normal speed walking as the physical task, while heart rate was measured using a wearable electrocardiogram recorder. After creating heart rate time series, a long short-term memory model was used to classify participants into frailty groups. In 5-fold cross validation evaluation, the long short-term memory model could classify the two above-mentioned frailty classes with a sensitivity, specificity, F1-score, and accuracy of 83.0%, 80.0%, 87.0%, and 82.0%, respectively. These findings showed that heart rate dynamics classification using long short-term memory without any feature engineering may provide an accurate and objective marker for frailty screening.

Physical and Cognitive Function Assessment to Predict Postoperative Outcomes of Abdominal Surgery.

BACKGROUND: Current evaluation methods to assess physical and cognitive function are limited and often not feasible in emergency settings. The upper-extremity function (UEF) test to assess physical and cognitive performance using wearable sensors. The purpose of this study was to examine the (1) relationship between preoperative UEF scores with in-hospital outcomes; and (2) association between postoperative UEF scores with 30-d adverse outcomes among adults undergoing emergent abdominal surgery. METHODS: We performed an observational, longitudinal study among adults older than 40 y who presented with intra-abdominal symptoms. The UEF tests included a 20-sec rapid repetitive elbow flexion (physical function), and a 60-sec repetitive elbow flexion at a self-selected pace while counting backwards by threes (cognitive function), administered within 24-h of admission and within 24-h prior to discharge. Multiple logistic regression models assessed the association between UEF and outcomes. Each model consisted of the in-hospital or 30-d post-discharge outcome as the dependent variable, preoperative UEF physical and cognitive scores as hypothesis covariates, and age and sex as adjuster covariates. RESULTS: Using UEF physical and cognitive scores to predict in-hospital outcomes, an area under curve (AUC) of 0.76 was achieved, which was 17% more sensitive when compared to age independently. For 30-d outcomes, the AUC increased to 0.89 when UEF physical and cognitive scores were included in the model with age and sex. DISCUSSION: Sensor-based measures of physical and cognitive function enhance outcome prediction providing an objective practicable tool for risk stratification in emergency surgery settings among aging adults presenting with intra-abdominal symptoms.

Nonlinear analysis of the movement variability structure can detect aging-related differences among cognitively healthy individuals.

Studying the dynamics of nonlinear systems can provide additional information about the variability structure of the system. Within the current study, we examined the application of regularity and local stability measures to capture motor function alterations due to dual-tasking using a previously validated upper-extremity function (UEF). We targeted young (ages 18 and 30 years) and older adults (65 years or older) with normal cognition based on clinical screening. UEF involved repetitive elbow flexion without counting (ST) and while counting backward by one (DT1) or three (DT3). We measured the regularity (measured by sample entropy (SE)), local stability (measured by the largest Lyapunov exponent (LyE)), as well as conventional peak-dependent variability measures (coefficient of variation of kinematics parameters) to capture motor dynamic alterations due to dual-tasking. Within both groups, only SE showed significant differences between all pairs of UEF condition comparisons, even ST vs DT1 (p = 0.007, effect size = 0.507), for which no peak-dependent parameter showed significant difference. Among all measures, the only parameter that showed a significant difference between young and older adults was LyE (p < 0.001, effect size = 0.453). Current findings highlight the potential of nonlinear analysis to detect aging-related alterations among cognitively healthy participants.

Dual-task performance is associated with brain MRI Morphometry in individuals with mild cognitive impairment.

BACKGROUND AND PURPOSE: Cognitive impairment is a critical health problem in the elderly population. Research has shown that patients with mild cognitive impairment (MCI) may develop dementia in later years. Therefore, early identification of MCI could allow for interventions to help delay the progression of this devastating disease. Our objective in this study was to detect the early presence of MCI in elderly patients via neuroimaging and dual-task performance. METHODS: Brain MRI scans from 21 older adult volunteers, including cognitively healthy adults (HA, n = 9, age = 68-79 years) and mild cognitively impaired (MCI, n = 12, age = 66-92 years) were analyzed using automatic segmentation techniques. Regional volume, surface area, and thickness measures were correlated with simultaneous performance of motor and cognitive tasks (dual-task) within a novel upper-extremity function (UEF) test, using multivariate analysis of variance models. RESULTS: We found significant associations of dual-task performance with volume of five cortical brain regions (P ≤ .048) and thickness of 13 regions (P ≤ .043) within the frontal, temporal, and parietal lobes. There was a significant interaction effect of cognitive group on dual-task score for the inferior temporal gyrus volume (P ≤ .034), and the inferior parietal lobule, inferior temporal gyrus, and middle temporal gyrus average thickness (P ≤ .037). CONCLUSIONS: This study highlighted the potential of dual-tasking and MRI morphometric changes as a simple and accurate tool for early detection of cognitive impairment among community-dwelling older adults. The strong interaction effects of cognitive group on UEF dual-task score suggest higher association between atrophy of these brain structures and compromised dual-task performance among the MCI group.

Frailty and heart response to physical activity.

BACKGROUND: Although previous studies showed that frail older adults are more susceptible to develop cardiovascular diseases, the underlying effect of frailty on heart rate dynamics is still unclear. The goal of the current study was to measure heart rate changes due to normal speed and rapid walking among non-frail and pre-frail/frail older adults, and to implement heart rate dynamic measures to identify frailty status. METHODS: Eighty-eight older adults (≥65 years) were recruited and stratified into frailty groups based on the five-component Fried frailty phenotype. While performing gait tests, heart rate was recorded using a wearable ECG and accelerometer sensors. Groups consisted of 27 non-frail (age = 78.70 ± 7.32) and 61 pre-frail/frail individuals (age = 81.00 ± 8.14). The parameters of interest included baseline heart rate measures (mean heart rate and heart rate variability), and heart rate dynamics due to walking (percentage change in heart rate and required time to reach the maximum heart rate). RESULTS: Respectively for normal and rapid walking conditions, pre-frail/frail participants had 46% and 44% less increase in heart rate, and 49% and 27% slower occurrence of heart rate peak, when compared to non-frail older adults (p < 0.04, effect size = 0.71 ± 0.12). Measures of heart rate dynamics showed stronger associations with frailty status compared to baseline resting-state measures (sensitivity = 0.75 and specificity = 0.65 using heart rate dynamics measures, compared to sensitivity = 0.64 and specificity = 0.62 using baseline parameters). CONCLUSIONS: These findings suggest that measures of heart rate dynamics in response to daily activities may provide meaningful markers for frailty screening.

Between-day repeatability of sensor-based in-home gait assessment among older adults: assessing the effect of frailty.

BACKGROUND: While sensor-based daily physical activity (DPA) gait assessment has been demonstrated to be an effective measure of physical frailty and fall-risk, the repeatability of DPA gait parameters between different days of measurement is not clear. AIMS: To evaluate test-retest reliability (repeatability) of DPA gait performance parameters, representing the quality of walking, and quantitative gait measures (e.g. number of steps) between two separate days of assessment among older adults. METHODS: DPA was acquired for 48-h from older adults (age ≥ 65 years) using a tri-axial accelerometer. Continuous walking bouts (≥ 60 s) were identified from acceleration data and used to extract gait performance parameters, including time- and frequency-domain gait parameters, representing walking speed, variability, and irregularity. To assess repeatability, intraclass correlation coefficient (ICC) was calculated using two-way mixed effects F-test models for day-1 vs. day-2 as the independent random effect. Repeatability tests were performed for all participants and also within frailty groups (non-frail and pre-frail/frail identified using Fried phenotype). RESULTS: Data was analyzed from 63 older adults (29 non-frail and 34 pre-frail/frail). Most of the time- and frequency-domain gait performance parameters showed good to excellent repeatability (ICC ≥ 0.70), while quantitative parameters, including number of steps and walking duration showed poor repeatability (ICC < 0.30). Among majority of the gait performance parameters, we observed higher repeatability among the pre-frail/frail group (ICC > 0.78) compared to non-frail individuals (0.39 < ICC < 0.55). CONCLUSION: Gait performance parameters, showed higher repeatability compared to quantitative measures. Higher repeatability among pre-frail/frail individuals may be attributed to a reduced functional capacity for performing more intense and variable physical tasks. TRIAL REGISTRATION: The clinical trial was retrospectively registered on June 18th, 2013 with ClinicalTrials.gov, identifier NCT01880229.

Comparison of wearable sensor to traditional methods in functional outcome measures: A systematic review.

Traditional methods of collecting functional outcome measures are widely used for lower extremity arthroplasty outcome assessment. Wearable sensors are emerging as viable tools for functional outcome measures in monitoring of postarthroplasty recovery. The objective of this review was to compare the efficacy of wearable sensors with traditional methods for monitoring postarthroplasty functional recovery. Articles were searched for inclusion in this review that used both traditional and wearable sensor functional outcome measures to assess lower extremity function before and after lower extremity arthroplasty. Two independent screeners reviewed all articles, and resolved differences through consensus and consultation with the senior author. Studies that met inclusion criteria were evaluated for methodologic quality using performed risk of bias assessments. Results from several traditional and wearable sensor functional outcome measures from baseline through follow-up were normalized across studies. Fourteen articles met the inclusion criteria. Six studies used statistical methods to directly compare functional outcome measures and eight studies used qualitative description of comparisons. This review found evidence that wearable sensors detected nuanced functional outcome information on the specific biomechanics and timing of recovery, which were unaccounted for using traditional methods. Wearable sensors have shown promising utility in providing additional recovery information from lower extremity arthroplasty compared with traditional functional outcome measures, but future research is needed to assess the clinical significance of this additional information. Wearable sensor technology is an emerging clinical tool providing advanced and determinative data with the potential for advancing the assessment of lower extremity arthroplasty outcomes.

Low-Rank Representation of Head Impact Kinematics: A Data-Driven Emulator.

Head motion induced by impacts has been deemed as one of the most important measures in brain injury prediction, given that the vast majority of brain injury metrics use head kinematics as input. Recently, researchers have focused on using fast approaches, such as machine learning, to approximate brain deformation in real time for early brain injury diagnosis. However, training such models requires large number of kinematic measurements, and therefore data augmentation is required given the limited on-field measured data available. In this study we present a principal component analysis-based method that emulates an empirical low-rank substitution for head impact kinematics, while requiring low computational cost. In characterizing our existing data set of 537 head impacts, each consisting of 6 degrees of freedom measurements, we found that only a few modes, e.g., 15 in the case of angular velocity, is sufficient for accurate reconstruction of the entire data set. Furthermore, these modes are predominantly low frequency since over 70% of the angular velocity response can be captured by modes that have frequencies under 40 Hz. We compared our proposed method against existing impact parametrization methods and showed significantly better performance in injury prediction using a range of kinematic-based metrics-such as head injury criterion (HIC), rotational injury criterion (RIC), and brain injury metric (BrIC)-and brain tissue deformation-based metrics-such as brain angle metric (BAM), maximum principal strain (MPS), and axonal fiber strains (FS). In all cases, our approach reproduced injury metrics similar to the ground truth measurements with no significant difference, whereas the existing methods obtained significantly different (p < 0.01) values as well as substantial differences in injury classification sensitivity and specificity. This emulator will enable us to provide the necessary data augmentation to build a head impact kinematic data set of any size. The emulator and corresponding examples are available on our website.