Footsteps and walking trajectories during the Timed Up and Go test in young, older, and Parkinson's disease subjects.

BACKGROUND: Footsteps and walking trajectories during the Timed Up and Go test (TUG), and their relationships with spatiotemporal gait parameters during turning in people with Parkinson's disease (PD) and older people have not been clarified. RESEARCH QUESTION: We investigated the footsteps, walking trajectories, and spatiotemporal parameters during the TUG in PD, healthy older (HO), and healthy young (HY) subjects and the associations between the parameters of footsteps or walking trajectories and the spatiotemporal parameters during turning. METHODS: Twenty-six PD, 20 HO, and 20 HY subjects participated. They performed the TUG at self-selected speed and underwent evaluations of spatiotemporal parameters in the forward, turning, and return phases and parameters of footsteps and walking trajectories by a system using laser range sensors to measure the two-dimensional distance data of the legs. Foot placement for each foot was measured as the estimated position when the leg speed of movement reached the minimum between foot-contact and foot-off. We calculated the minimum distance from a TUG marker to footsteps and the maximum anterior distance from the start to the footsteps. Step length was calculated using a method for non-linear walking. RESULTS: The PD subjects showed significantly smaller step lengths in all phases. The minimum distance from the marker to the footsteps in PD subjects was significantly smaller than in HO subjects and was significantly positively correlated only with the turning-phase step length. The maximum anterior distance from the start to footsteps in HO subjects was significantly larger than in PD and HY subjects and was not correlated with any spatiotemporal parameters. SIGNIFICANCE: This study demonstrated that people with PD turn close to the TUG marker, and this turning strategy may be associated with the decreased step length when turning. These findings could help in providing instructions which prevent the exaggeration of step-length reduction when turning.

Hip abductor muscle weakness and slowed turning motion in people with knee osteoarthritis.

Laser range sensor-based timed up and go (laser-TUG) test can evaluate performance in TUG subtasks (sit-to-walk [STW], walking a short distance, and turning). This study aimed to test the hypothesis that weaker hip abductor muscle strength is more significantly associated with slowed turning speed than with the other TUG subtasks (STW and straight walking) after controlling for quadriceps muscle strength in patients with knee osteoarthritis (OA). Community-dwelling participants with knee OA (Kellgren and Lawrence [K&L] grade ≥ 1; mean age, 68.6 years; 70.3% women) underwent laser-TUG. Spatiotemporal gait parameters in TUG and the TUG subtasks were evaluated as outcome measures. The isometric muscle strength of the hip abductor and quadriceps was measured using a hand-held dynamometer. Multiple linear regression analysis was performed to examine the relationship between muscle strength as an independent variable and spatiotemporal parameters as dependent variables. The relative importance of hip abductor muscle strength was determined using the percentages of unique variance. Participants with weaker hip abductor muscle strength demonstrated 0.094 m/s slower turning speed after adjustment for covariates including quadriceps muscle strength. The unique variance explained by hip abductor muscle strength in turning speed was 2.1%. However, no significant relationships were confirmed between weak hip abductor muscle strength and the time to perform TUG and the straight walking (forward and return) phase. These findings indicate that turning motion may be more sensitive to aggravated hip abductor muscle weakness and may show better response to hip muscle strengthening exercises. Longitudinal studies are warranted to elucidate this issue.

Estimation of Vertical Ground Reaction Force Using Low-Cost Insole With Force Plate-Free Learning From Single Leg Stance and Walking.

For the evaluation of pathological gait, a machine learning-based estimation of the vertical ground reaction force (vGRF) using a low-cost insole is proposed as an alternative to costly force plates. However, learning a model for estimation still relies on the use of force plates, which is not accessible in small clinics and individuals. Therefore, this paper presents a force plate-free learning from a single leg stance (SLS) and natural walking measured only by the insoles. This method used a linear least squares regression that fits insole measurements during SLS to body weight in order to learn a model to estimate vGRF during walking. Constraints were added to the regression so that vGRF estimates during walking were of proper magnitude, and the constraint bounds were newly defined as a linear function of stance duration. Moreover, a lower bound for the estimated vGRF in mid-stance was added to the constraints to enhance estimation accuracy. The vGRF estimated by the proposed method was compared with force platforms for 4 healthy young adults and 13 elderly adults including patients with mild osteoarthritis, knee pain, and valgus hallux. Through the experiments, the proposed learning method had a normalized root mean squared error under 10% for healthy young and elderly adults with stance durations within a certain range (600-800 ms). From these results, the validity of the proposed learning method was verified for various users requiring assessment in the field of medicine and healthcare.

Markerless Knee Joint Position Measurement Using Depth Data during Stair Walking.

Climbing and descending stairs are demanding daily activities, and the monitoring of them may reveal the presence of musculoskeletal diseases at an early stage. A markerless system is needed to monitor such stair walking activity without mentally or physically disturbing the subject. Microsoft Kinect v2 has been used for gait monitoring, as it provides a markerless skeleton tracking function. However, few studies have used this device for stair walking monitoring, and the accuracy of its skeleton tracking function during stair walking has not been evaluated. Moreover, skeleton tracking is not likely to be suitable for estimating body joints during stair walking, as the form of the body is different from what it is when it walks on level surfaces. In this study, a new method of estimating the 3D position of the knee joint was devised that uses the depth data of Kinect v2. The accuracy of this method was compared with that of the skeleton tracking function of Kinect v2 by simultaneously measuring subjects with a 3D motion capture system. The depth data method was found to be more accurate than skeleton tracking. The mean error of the 3D Euclidian distance of the depth data method was 43.2 ± 27.5 mm, while that of the skeleton tracking was 50.4 ± 23.9 mm. This method indicates the possibility of stair walking monitoring for the early discovery of musculoskeletal diseases.

Association between mild cognitive impairment and trajectory-based spatial parameters during timed up and go test using a laser range sensor.

BACKGROUND: The Timed Up and Go (TUG) test may be a useful tool to detect not only mobility impairment but also possible cognitive impairment. In this cross-sectional study, we used the TUG test to investigate the associations between trajectory-based spatial parameters measured by laser range sensor (LRS) and cognitive impairment in community-dwelling older adults. METHODS: The participants were 63 community-dwelling older adults (mean age, 73.0 ± 6.3 years). The trajectory-based spatial parameters during the TUG test were measured using an LRS. In each forward and backward phase, we calculated the minimum distance from the marker, the maximum distance from the x-axis (center line), the length of the trajectories, and the area of region surrounded by the trajectory of the center of gravity and the x-axis (center line). We measured mild cognitive impairment using the Mini-Mental State Examination score (26/27 was the cut-off score for defining mild cognitive impairment). RESULTS: Compared with participants with normal cognitive function, those with mild cognitive impairment exhibited the following trajectory-based spatial parameters: short minimum distance from the marker (p = 0.044), narrow area of center of gravity in the forward phase (p = 0.012), and a large forward/whole phase ratio of the area of the center of gravity (p = 0.026) during the TUG test. In multivariate logistic regression analyses, a short minimum distance from the marker (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.69-0.98), narrow area of the center of gravity in the forward phase (OR: 0.01, 95% CI: 0.00-0.36), and large forward/whole phase ratio of the area of the center of gravity (OR: 0.94, 95% CI: 0.88-0.99) were independently associated with mild cognitive impairment. CONCLUSIONS: In conclusion, our results indicate that some of the trajectory-based spatial parameters measured by LRS during the TUG test were independently associated with cognitive impairment in older adults. In particular, older adults with cognitive impairment exhibit shorter minimum distances from the marker and asymmetrical trajectories during the TUG test.

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PURPOSE: The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. METHODS: This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. RESULTS: In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. CONCLUSION: We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test.

Improved Leg Tracking Considering Gait Phase and Spline-Based Interpolation during Turning Motion in Walk Tests.

Falling is a common problem in the growing elderly population, and fall-risk assessment systems are needed for community-based fall prevention programs. In particular, the timed up and go test (TUG) is the clinical test most often used to evaluate elderly individual ambulatory ability in many clinical institutions or local communities. This study presents an improved leg tracking method using a laser range sensor (LRS) for a gait measurement system to evaluate the motor function in walk tests, such as the TUG. The system tracks both legs and measures the trajectory of both legs. However, both legs might be close to each other, and one leg might be hidden from the sensor. This is especially the case during the turning motion in the TUG, where the time that a leg is hidden from the LRS is longer than that during straight walking and the moving direction rapidly changes. These situations are likely to lead to false tracking and deteriorate the measurement accuracy of the leg positions. To solve these problems, a novel data association considering gait phase and a Catmull-Rom spline-based interpolation during the occlusion are proposed. From the experimental results with young people, we confirm   that the proposed methods can reduce the chances of false tracking. In addition, we verify the measurement accuracy of the leg trajectory compared to a three-dimensional motion analysis system (VICON).

Gait measurement system for the multi-target stepping task using a laser range sensor.

For the prevention of falling in the elderly, gait training has been proposed using tasks such as the multi-target stepping task (MTST), in which participants step on assigned colored targets. This study presents a gait measurement system using a laser range sensor for the MTST to evaluate the risk of falling. The system tracks both legs and measures general walking parameters such as stride length and walking speed. Additionally, it judges whether the participant steps on the assigned colored targets and detects cross steps to evaluate cognitive function. However, situations in which one leg is hidden from the sensor or the legs are close occur and are likely to lead to losing track of the legs or false tracking. To solve these problems, we propose a novel leg detection method with five observed leg patterns and global nearest neighbor-based data association with a variable validation region based on the state of each leg. In addition, methods to judge target steps and detect cross steps based on leg trajectory are proposed. From the experimental results with the elderly, it is confirmed that the proposed system can improve leg-tracking performance, judge target steps and detect cross steps with high accuracy.