Vicon Nexus Research Articles

A SIX-LINK KINEMATIC CHAIN MODEL OF HUMAN BODY USING KANE'S METHOD

A biomechanics model of six-link kinematic chain of human body is developed by using Kane's method. The kinematic data comprise of six segments; foot, calf, thigh, trunk, upper arm and forearm, are obtained through data collection of walking, running and jumping using the Vicon Nexus system. The motion capture system uses 12 Vicon MX-3+ cameras and 12 Vicon MX-F40 cameras, two DV (50 Hz) cameras and a force plate (100 Hz). Inverse dynamics approach is used to obtain the unknown value of torques produced by joint segments during walking, running and jumping activities. The results show that the largest value of torques produced occurs at the foot segment.

Pelvic Induced Trunk Posture Limits Shoulder ROM and Trunk Rotation

Exaggerated kyphosis and protracted shoulder postures increase scapular anterior tilt, abduction and lateral rotation compromising shoulder function. Excessive posterior tilt increases spinal flexion and shoulder protraction altering the arthrokinematics of the intervertebral joints. Shoulder motion combined with trunk rotation is thus likely affected by spinal posture which has implications for sport performance, injury and shoulder dysfunction. PURPOSE: To determine the effect of trunk posture on arm flexion, abduction, and trunk rotation ranges of motion (ROM). Method: Twenty-two healthy college students free of recent shoulder or spinal injury gave written informed consent. An 8 segment model of the upper body: head, spine, pelvis and both scapulae, clavicles, and humeri, was created. Three movement tasks (arm abduction, flexion, and trunk rotation) in 3 sitting trunk postures (neutral (N), full posterior tilt (P), and full anterior tilt (A)) were recorded using Vicon Nexus and analyzed in Visual3D. Movements were repeated right and left. Differences in arm abduction, flexion, and trunk rotation ROM were assessed across postures with one-way repeated measures ANOVAs. RESULTS: Average pelvic tilt and trunk flexion, respectively, were -1 ± 7° and 4 ± 7° for A, -10 ± 7° and 4 ± 8° for N, and -21 ± 7°and 21 ± 15° for P; positive values are anterior tilt/flexion. Arm abduction, flexion, and right trunk rotation ROM were all reduced in P as compared to N and A with arm abduction decreasing the most (Table). CONCLUSIONS: Sitting trunk posture does effect active arm ROM and trunk rotation in healthy subjects. Future research should examine the effect of trunk postures on similar movements performed during sports such as a golf drive.Table: Arm and Trunk ROM.

Interlimb Coordination Patterns in People with Parkinson's Disease

Efficient human walking requires the coordinated function of both the upper and lower extremities. In healthy adults as walking speeds reach 0.8 m/s and above, the arms transition from an in-phase relationship to an out-of-phase relationship with each other. Further, arm swing synchronizes with the stride frequency of the contralateral leg. It is well documented that people with Parkinson's disease (PD) show diminished arm swing during normal walking and that this may be one factor contributing to the increased falls in this population. Yet, it is unknown whether the reduction in arm swing affects interlimb coordination patterns in this specific population. PURPOSE: To investigate the interlimb coordination patterns present in people with PD during normal walking and to compare these patterns to age matched healthy older adults walking at similar speeds. METHODS: Eighteen individuals with Parkinson's disease and nine age (± 2 years) and gait velocity (±0.1 m/s) matched healthy older adults participated. Kinematic data of overground walking trials were collected utilizing a 12 camera Vicon motion capture system (Vicon Nexus, Oxford, UK). Arm and leg coordination was quantified by determining point estimate of relative phase and covariance measures. Point estimate of relative phase was calculated as the phase difference in time of maximum shoulder flexion and maximum hip flexion divided by duration of the stride cycle. Independent samples t-tests were run to analyze between-group differences. RESULTS: Comparatively, the persons with PD showed statistical reductions in comparing hip-shoulder covariance of the affected shoulder and contralateral hip compared to the healthy controls (p=.016). The persons with PD also exhibited large differences in PERP measures in comparison to the control group. The mean PERP value for the PD group was 33° compared to 9° in the control group, however, only a statistical trend could be identified (p=.077). CONCLUSION: Evidence shows that PD causes reduction in interlimb coordination patterns. The reductions in coordination may attribute to the changes seen in gait patterns as the disease progresses and risks for falling.

Walking with Concurrent Cognitive Tasks in People with Traumatic Brain Injury

PURPOSE: To investigate the influence of concurrent cognitive tasks on gait performance in people with TBI. METHODS: A total of 9 people with TBI (age: 41.9 ± 10.6) and 9 healthy controls (42.8 ± 11.1) participated in this study. All were asked to complete 20-meter walking course while performing various types of concurrent cognitive tasks. Each participant was asked to walk at their maximum speed in 4 test conditions: a) simple walking (W), b) walking with word generation (WWG-walking and citing words starting with a randomly assigned alphabet letter), c) walking with answering questions (WQA - walking and answering questions based on personal information gathered in advance), and d) walking with performing visual tasks (WVT - walking and performing 3 visual tasks involving directional sign, shape and spatial recognition). All walking trials were captured by 3D motion analysis system (Vicon Nexus) for gait analysis. A Bluetooth headset was used for walking trials which involved any verbal communication. Repeated measures mix model ANOVA was used to examine any alterations in gait variables. RESULTS: Non-TBI group showed significant decreases in walking speed (10.84% and 10.24% decreases respectively) and stride length (6.96% and 6.33% decreases respectively) while performing WWG and WQA as compared to W (all ps <.05). TBI group demonstrated significant decreases in walking speed (30.77% decrease), stride length (18.12% decrease) and hip ROM (14.12% decrease) during WWG performance as compared to W while it showed an increase in stance phase percentage (7.91% increase) with WWG (all ps <.05). Only the affected limb changed kinematics of the hip joint significantly decreasing its excursion from 38.32 ± 13.28 degrees to 32.91±12.11 degrees (p<.031). Significant group interactions were found in walking speed, stride length and stance phase percentage, where TBI group showed greater changes in those gait variables CONCLUSIONS: People with TBI have more difficulty in performing multiple tasks involving cognitive functions while walking as compared to those without TBI. The findings suggest that the use of various configurations of walking and talking or other cognitive tasks can be more effective for improving functional gait of people with TBI rather than simple practice of walking.

Adaptation Strategies to Split-Belt Treadmill Walking in Healthy Young Adults

Human gait must be highly adaptable in order to maintain dynamic stability as we move through varying external environments. Split-belt treadmills provide an opportunity to create challenging locomotor patterns and have recently been used to evaluate adaptation patterns during walking. Healthy young adults (HYA) adapt to split-belt treadmill walking (SBTW) by adjusting spatiotemporal patterns asymmetrically to match the task demands of the treadmill; however, while a basic adaptation pattern has been established among HYA, it remains unknown whether more specific adaptation strategies exist. PURPOSE: To characterize the different individual spatiotemporal adaptation strategies HYA use during SBTW. METHODS: Ten HYA (23 ± 4 yrs) walked on a split-belt treadmill, first with the belts moving together at 50% of the participant's self-selected "fast" velocity for two minutes (tied) and then with the dominant limb belt sped up to the "fast" velocity (split) for 10 minutes. Kinematic data of the last 30 seconds of each trial were collected using a 12-camera Vicon Nexus motion capture system (Vicon Nexus, Oxford, UK). Stride length and swing/stance ratio were calculated from manually-labeled gait events. Z-scores were calculated for the bilateral symmetry change (BSC) of these two parameters from the symmetrical condition to the asymmetrical condition. BSC was calculated as the difference in the percent change of bilateral symmetry (fast limb parameter divided by the slow limb parameter) from the tied condition to the split condition. The five fastest walkers (self-selected "fast" walking speed > 1.4 m/s) and five slowest walkers (self-selected "fast" walking speed ≤ 1.4 m/s) were separated into two groups and independent-samples t-tests were run to analyze between-group differences for BSC of swing/stance ratio and BSC of stride length. RESULTS: The slower walkers showed lower z-scores for BSC of swing/stance ratio (-.75 ±.44 vs.75 ±.81, p =.004) and higher z-scores for BSC of stride length (.54 ±.40 vs. -.80 ±.65, p =.006) when compared to the faster walkers. CONCLUSION: There appear to be at least two different spatiotemporally-driven adaptation approaches to SBTW and these may be related to walking speed.

Surface Electromyographic Activation Patterns and Elbow Joint Motion During a Pull-Up, Chin-Up, or Perfect-Pullup™ Rotational Exercise

This study compared a conventional pull-up and chin-up with a rotational exercise using Perfect·Pullup™ twisting handles. Twenty-one men (24.9 ± 2.4 years) and 4 women (23.5 ± 1 years) volunteered to participate. Electromyographic (EMG) signals were collected with DE-3.1 double-differential surface electrodes at a sampling frequency of 1,000 Hz. The EMG signals were normalized to peak activity in the maximum voluntary isometric contraction (MVIC) trial and expressed as a percentage. Motion analysis data of the elbow were obtained using Vicon Nexus software. One-factor repeated measures analysis of variance examined the muscle activation patterns and kinematic differences between the 3 pull-up exercises. Average EMG muscle activation values (%MVIC) were as follows: latissimus dorsi (117-130%), biceps brachii (78-96%), infraspinatus (71-79%), lower trapezius (45-56%), pectoralis major (44-57%), erector spinae (39-41%), and external oblique (31-35%). The pectoralis major and biceps brachii had significantly higher EMG activation during the chin-up than during the pull-up, whereas the lower trapezius was significantly more active during the pull-up. No differences were detected between the Perfect·Pullup™ with twisting handles and the conventional pull-up and chin-up exercises. The mean absolute elbow joint range of motion was 93.4 ± 14.6°, 100.6 ± 14.5°, and 99.8 ± 11.7° for the pull-up, chin-up, and rotational exercise using the Perfect·Pullup™ twisting handles, respectively. For each exercise condition, the timing of peak muscle activation was expressed as a percentage of the complete pull-up cycle. A general pattern of sequential activation occurred suggesting that pull-ups and chin-ups were initiated by the lower trapezius and pectoralis major and completed with biceps brachii and latissimus dorsi recruitment. The Perfect·Pullup™ rotational device does not appear to enhance muscular recruitment when compared to the conventional pull-up or chin-up.

3D joint kinematics by means of wearable sensors

There appears a linear relationship between small increases in running speed and cardiovascular health benefits. Encouraging or coaching recreational runners to increase their running speed to derive these health benefits might be more effective if their joint level kinematic and kinetic strategy was understood. The aim of this investigation was to compare the peak sagittal plane motions, moments, and powers of the hip, knee and ankle at 85%, 100%, 115% and 130% of self-selected running speed. Overground running data were collected in 12 recreational runners (6 women, 6 men) with a full body marker set using a 12-camera Vicon MX system with an AMTI force plate. Kinematics and kinetics were analyzed with Vicon Nexus software. Participants chose to run at 2.6 ± 0.5 m/s (85%); 3.0 ± 0.5 m/s (100%); 3.3 ± 0.5 m/s (115%); and 3.7 ± 0.5 m/s (130%); these four speeds approximately correspond to 6:24-, 5:33-, 5:03-, and 4:30-min kilometer running paces. Running speed had a significant effect (P < 0.05) on peak kinematic and kinetic variables of the hips, knees and ankles, with peak sagittal hip moments invariant (P > 0.54) and the peak sagittal ankle power generation (P < 0.0001) the most highly responsive variable. The timing of the peak sagittal extensor moments and powers at the hip, knee and ankle were distributed across stance in a sequential manner. This study shows that running speed affects lower limb joint kinematics and kinetics and suggests that specific intersegmental kinetic strategies might exist across the narrow range of running speeds.