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.

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.

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.

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.

Interpersonal motor synergy: coworking strategy depends on task constraints.

We investigated the role of task constraints on interpersonal interactions. Twenty-one pairs of coworkers performed a finger force production task on force sensors placed at two ends of a seesaw-like apparatus and matched a combined target force of 20 N for 23 s over 10 trials. There were two experimental conditions: 1) FIXED: the seesaw apparatus was mechanically held in place so that the only task constraint was to match the 20 N resultant force, and 2) MOVING: the lever in the apparatus was allowed to rotate freely around its fulcrum, acting like a seesaw, so an additional task constraint to (implicitly) balance the resultant moment was added. We hypothesized that the additional task constraint of moment stabilization imposed on the MOVING condition would deteriorate task performance compared with the FIXED condition; however, this was rejected, as the performance of the force matching task was similar between two conditions. We also hypothesized that the central nervous systems (CNSs) would employ distinct coworking strategies or interpersonal motor synergy (IPMS) between conditions to satisfy different task constraints, which was supported by our results. Negative covariance between coworker's forces in the FIXED condition suggested a force stabilization strategy, whereas positive covariance in the MOVING condition suggested a moment stabilization strategy, implying that independent CNSs adopt distinct IPMSs depending on task constraints. We speculate that in the absence of a central neural controller, shared visual and mechanical connections between coworkers may suffice to trigger modulations in the cerebellum of each CNS to satisfy competing task constraints.NEW & NOTEWORTHY To the best of our knowledge, this is the first study to investigate the coworking behavior or IPMS when an additional task constraint is imposed. Our proposed analytical framework quantifies IPMS and allows for investigating variability in offline (i.e., across multiple repetitions) and online (i.e., across time) control, which is novel in coworking research. Understanding variability while performing a task is essential, as repeating a task is not always possible, as in therapeutic contexts.

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.

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.

Sensor-based characterization of daily walking: a new paradigm in pre-frailty/frailty assessment.

BACKGROUND: Frailty is a highly recognized geriatric syndrome resulting in decline in reserve across multiple physiological systems. Impaired physical function is one of the major indicators of frailty. The goal of this study was to evaluate an algorithm that discriminates between frailty groups (non-frail and pre-frail/frail) based on gait performance parameters derived from unsupervised daily physical activity (DPA). METHODS: DPA was acquired for 48 h from older adults (≥65 years) using a tri-axial accelerometer motion-sensor. Continuous bouts of walking for 20s, 30s, 40s, 50s and 60s without pauses were identified from acceleration data. These were then used to extract qualitative measures (gait variability, gait asymmetry, and gait irregularity) and quantitative measures (total continuous walking duration and maximum number of continuous steps) to characterize gait performance. Association between frailty and gait performance parameters was assessed using multinomial logistic models with frailty as the dependent variable, and gait performance parameters along with demographic parameters as independent variables. RESULTS: One hundred twenty-six older adults (44 non-frail, 60 pre-frail, and 22 frail, based on the Fried index) were recruited. Step- and stride-times, frequency domain gait variability, and continuous walking quantitative measures were significantly different between non-frail and pre-frail/frail groups (p < 0.05). Among the five different durations (20s, 30s, 40s, 50s and 60s), gait performance parameters extracted from 60s continuous walks provided the best frailty assessment results. Using the 60s gait performance parameters in the logistic model, pre-frail/frail group (vs. non-frail) was identified with 76.8% sensitivity and 80% specificity. DISCUSSION: Everyday walking characteristics were found to be associated with frailty. Along with quantitative measures of physical activity, qualitative measures are critical elements representing the early stages of frailty. In-home gait assessment offers an opportunity to screen for and monitor frailty. TRIAL REGISTRATION: The clinical trial was retrospectively registered on June 18th, 2013 with ClinicalTrials.gov, identifier NCT01880229.

Can motor function uncertainty and local instability within upper-extremity dual-tasking predict amnestic mild cognitive impairment and early-stage Alzheimer's disease?

In this study, we examined the uncertainty and local instability of motor function for cognitive impairment screening using a previously validated upper-extremity function (UEF). This approach was established based upon the fact that elders with an impaired executive function have trouble in the simultaneous execution of a motor and a cognitive task (dual-tasking). Older adults aged 65 years and older were recruited and stratified into 1) cognitive normal (CN), 2) amnestic MCI of the Alzheimer's type (aMCI), and 3) early-stage Alzheimer's Disease (AD). Participants performed normal-paced repetitive elbow flexion without counting and while counting backward by ones and threes. The influence of cognitive task on motor function was measured using uncertainty (measured by Shannon entropy), and local instability (measured by the largest Lyapunov exponent) of elbow flexion and compared between cognitive groups using ANOVAs, while adjusting for age, sex, and BMI. We developed logistic ordinal regression models for predicting cognitive groups based on these nonlinear measures. A total of 81 participants were recruited, including 35 CN (age = 83.8 ± 6.9), 30 aMCI (age = 83.9 ± 6.9), and 16 early AD (age = 83.2 ± 6.6). Uncertainty of motor function demonstrated the strongest associations with cognitive impairment, with an effect size of 0.52, 0.88, and 0.51 for CN vs. aMCI, CN vs. AD, and aMCI vs. AD comparisons, respectively. Ordinal logistic models predicted cognitive impairment (aMCI and AD combined) with a sensitivity and specificity of 0.82. The findings accentuate the potential of employing nonlinear dynamical features of motor functions during dual-tasking, especially uncertainty, in detecting cognitive impairment.

Sensor-Based Upper-Extremity Frailty Assessment for the Vascular Surgery Risk Stratification.

BACKGROUND: Available methods for determining outcomes in vascular surgery patients are often subjective or not applicable in nonambulatory patients. The purpose of the present study was to assess the association between vascular surgery outcomes and a previously validated upper-extremity function (UEF) method, which incorporates wearable motion sensors for the physical frailty assessment. MATERIALS AND METHODS: Patients (≥50 y old) undergoing vascular surgery were recruited. Participants performed the 20-s UEF test, which involved rapid elbow flexion. This technology quantifies physical frailty features including slowness, weakness, exhaustion, and flexibility, which allows grouping individuals into nonfrail, prefrail, and frail categories. Surgical outcomes included length of hospital stay, discharged disposition, and 30-d mortality, complications, readmission, and reintervention(s). Associations between outcomes and frailty were assessed using nominal logistic regression models, adjusted for age, gender, body mass index, and wound classification. RESULTS: Thirty-seven participants were recruited: eight nonfrail (age = 62.0 ± 10.6); 22 prefrail (age = 65.6 ± 11.6); and seven frail (age = 68.0 ± 8.0). Significant associations were observed between frailty and length of hospital stay (three times longer among frail participants, P = 0.03), mortality after surgery (two incidents among frail participants, P < 0.01), and adverse discharge disposition (all nonfrail patients were discharged home, whereas only 43% of frail patients discharged home, P = 0.01). CONCLUSIONS: This is the first study to validate the utility of UEF among patients undergoing any vascular surgery. Findings suggest that UEF may provide an objective and simple approach for assessing frailty to predict adverse events after vascular surgery, especially for nonambulatory patients.

Screening older adults for amnestic mild cognitive impairment and early-stage Alzheimer's disease using upper-extremity dual-tasking.

The purpose of the current study was to develop an objective tool based on dual-task performance for screening early-stage Alzheimer's disease (AD) and mild cognitive impairment (MCI of the Alzheimer's type). Dual-task involved a simultaneous execution of a sensor-based upper-extremity function (UEF) motor task (normal or rapid speed) and a cognitive task of counting numbers backward (by ones or threes). Motor function speed and variability were recorded and compared between cognitive groups using ANOVAs, adjusted for age, gender, and body mass index. Cognitive indexes were developed using multivariable ordinal logistic models to predict the cognitive status using UEF parameters. Ninety-one participants were recruited; 35 cognitive normal (CN, age = 83.8 ± 6.9), 34 MCI (age = 83.9 ± 6.6), and 22 AD (age = 84.1 ± 6.1). Flexion number and sensor-based motion variability parameters, within the normal pace elbow flexion, showed significant between-group differences (maximum effect size of 1.10 for CN versus MCI and 1.39 for CN versus AD, p < 0.0001). Using these parameters, the cognitive status (both MCI and AD) was predicted with a receiver operating characteristic area under curve of 0.83 (sensitivity = 0.82 and specificity = 0.72). Findings suggest that measures of motor function speed and accuracy within a more practical upper-extremity test (instead of walking) may provide enough complexity for cognitive impairment assessment.

The association between cognition and dual-tasking among older adults: the effect of motor function type and cognition task difficulty.

BACKGROUND: Dual-task actions challenge cognitive processing. The usefulness of objective methods based on dual-task actions to identify the cognitive status of older adults has been previously demonstrated. However, the properties of select motor and cognitive tasks are still debatable. We investigated the effect of cognitive task difficulty and motor task type (walking versus an upper-extremity function [UEF]) in identifying cognitive impairment in older adults. METHODS: Older adults (≥65 years) were recruited, and cognitive ability was measured using the Montreal Cognitive Assessment (MoCA). Participants performed repetitive elbow flexion under three conditions: 1) at maximum pace alone (Single-task); and 2) while counting backward by ones (Dual-task 1); and 3) threes (Dual-task 2). Similar single- and dual-task gait were performed at normal speed. Three-dimensional kinematics were measured for both motor functions using wearable sensors. RESULTS: One-hundred older adults participated in this study. Based on MoCA score <20, 21 (21%) of the participants were considered cognitively impaired (mean age =86±10 and 85±5 for cognitively impaired and intact participants, respectively). Within ANOVA models adjusted with demographic information, UEF dual-task parameters, including speed and range-of-motion variability were significantly higher by 52% on average, among cognitively impaired participant (p<0.01). Logistic models with these UEF parameters plus age predicted cognitive status with sensitivity, specificity, and area under curve (AUC) of 71%, 81% and 0.77 for Dual-task 1. The corresponding values for UEF Dual-task 2 were 91%, 73% and 0.81, respectively. ANOVA results were non-significant for gait parameters within both dual-task conditions (p>0.26). CONCLUSION: This study demonstrated that counting backward by threes within a UEF dual-task experiment was a pertinent and challenging enough task to detect cognitive impairment in older adults. Additionally, UEF was superior to gait as the motor task component of the dual-task. The UEF dual-task could be applied as a quick memory screen in a clinical setting.

Upper-extremity function prospectively predicts adverse discharge and all-cause COPD readmissions: a pilot study.

BACKGROUND: Frailty can inform management approaches for individuals with COPD. However, inpatient measures of frailty are seldom employed because they are time-consuming or inapplicable for bed-bound patients. We investigated the feasibility and potential of an innovative sensor-based upper-extremity function (UEF) test for frailty assessment in predicting adverse outcomes. METHODS: Hospitalized patients with COPD-related exacerbations (aged ≥55 years) were recruited and performed the UEF test within 24 hours of admission. UEF parameters were obtained and fed into our previously developed frailty model to calculate frailty status (non-frail, pre-frail, and frail) and frailty score (0: extreme resilience to 1: extreme frailty). In-hospital (length of stay) and post-discharge (discharge disposition, 30-day exacerbation with treatment, and all-cause 30-day readmission) outcomes were collected. Associations between UEF frailty and outcomes were investigated using ANOVA and logistic models adjusted for demographic data. RESULTS: In total, 42 patients were recruited. All participants were able to perform the UEF test. Based on UEF, participants were stratified into three groups of non-frail (n=6, frailty score =0.18±0.09), pre-frail (n=14, frailty score =0.45±0.09), and frail (n=22, frailty score =0.78±0.11). Both frailty status and frailty score were significantly associated with unfavorable discharge disposition (P<0.005) and all-cause 30-day readmission (P<0.05). On the other hand, UEF frailty measures were associated with neither hospital length of stay (P>0.5) nor 30-day exacerbation with treatment (P>0.70). Age was only significantly associated with unfavorable discharge disposition (P=0.048). CONCLUSION: In agreement with previous work, the current findings underline the importance of measuring frailty for risk-stratification of COPD patients. The UEF was feasible and easily performed among all hospitalized COPD patients. In this study, we have shown that, using our quick and objective frailty measures, COPD patients can be prospectively risk-stratified in terms of unfavorable discharge disposition and all-cause 30-day readmissions.

Proprioceptive impairments in high fall risk older adults: the effect of mechanical calf vibration on postural balance.

BACKGROUND: Impairments in proprioceptive mechanism with aging has been observed and associated with fall risk. The purpose of the current study was to assess proprioceptive deficits among high fall risk individuals in comparison with healthy participants, when postural performance was disturbed using low-frequency mechanical gastrocnemius vibratory stimulation. METHODS: Three groups of participants were recruited: healthy young (n = 10; age = 23 ± 2 years), healthy elders (n = 10; age = 73 ± 3 years), and high fall risk elders (n = 10; age = 84 ± 9 years). Eyes-open and eyes-closed upright standing balance performance was measured with no vibration, and 30 and 40 Hz vibration of both calves. Vibration-induced changes in balance behaviors, compared to baseline (no vibratory stimulation) were compared between three groups using multivariable repeated measures analysis of variance models. RESULTS: Overall, similar results were observed for two vibration frequencies. However, changes in body sway due to vibration were more obvious within the eyes-closed condition, and in the medial-lateral direction. Within the eyes-closed condition high fall risk participants showed 83% less vibration-induced change in medial-lateral body sway, and 58% less sway velocity, when compared to healthy participants (p < 0.001; effect size = 0.45-0.64). CONCLUSIONS: The observed differences in vibration effects on balance performance may be explained by reduced sensitivity in peripheral nervous system among older adults with impaired balance.

The influence of mechanical vibration on local and central balance control.

Fall prevention has an indispensable role in enhancing life expectancy and quality of life among older adults. The first step to prevent falls is to devise reliable methods to identify individuals at high fall risk. The purpose of the current study was to assess alterations in local postural muscle and central sensory balance control mechanisms due to low-frequency externally applied vibration among elders at high fall risk, in comparison with healthy controls, as a potential tool for assessing fall risk. Three groups of participants were recruited: healthy young (n = 10; age = 23 ±â€¯2 years), healthy elders (n = 10; age = 73 ±â€¯3 years), and elders at high fall risk (n = 10; age = 84 ±â€¯9 years). Eyes-open and eyes-closed upright standing balance performance was measured with no vibration, 30 Hz, and 40 Hz vibration of Gastrocnemius muscles. When vibratory stimulation was applied, changes in local-control performance manifested significant differences among the groups (p < 0.01). On average between conditions, we observed 97% and 92% less change among high fall risk participants when compared to healthy young and older adults, respectively. On the other hand, vibration-induced changes in the central-control performance were not significant between groups (p ≥ 0.19). Results suggest that local-control deficits are responsible for balance behavior alterations among elders at high fall risk and healthy individuals. This observation may be attributable to deterioration of short-latency reflexive loop in elders at high fall risk. On the other hand, we could not ascribe the balance alterations to problems related to central nervous system performance or long-latency responses.

Beneficial effects of L-arginine on 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced neuronal degeneration in substantia nigra of Balb/c mice.

BACKGROUND: L-arginine has been recently investigated and proposed to reduce neurological damage after various experimental models of neuronal cellular damage. In this study, we aim to evaluate the beneficial effects of L-arginine administration on the numerical density of dark neurons (DNs) in the substantia nigra pars compacta (SNc) of Balb/c mice subjected to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) administration. MATERIALS AND METHODS: Male Balb/c mice were randomly divided into 4 groups (n = 7 each): MPTP only; saline only (control); MPTP + L-arginine; and L-arginine only. The animals were infused intranasally with a single intranasal administration of the proneurotoxin MPTP (1 mg/nostril). L-arginine (300 mg/kg) was administrated intraperitoneally once daily for 1-week starting from 3 days after MPTP administration. Cavalieri principle method was used to estimate the numerical density of DNs in the SNc of different studied groups. RESULTS: Twenty days following MPTP administration, the number of DNs was significantly increased when compared to sham-control and L-arginine-control groups (P < 0.05). Nevertheless, our results showed that L-arginine administration significantly decreased the numerical density of DNs in SNc of mice. CONCLUSION: This investigation provides new insights in experimental models of Parkinson's disease, indicating that L-arginine represents a potential treatment agent for dopaminergic neuron degeneration in SNc observed in Parkinson's disease patients.

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange-Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.