Fractal dynamics of body motion in post-stroke hemiplegic patients during walking

Effects of ankle-foot orthoses on gait parameters in post-stroke patients with different Brunnstrom stages of the lower limb: a single-center crossover trial

BACKGROUND

Ankle-foot orthoses (AFO) can improve gait posture and walking ability in post-stroke patients. However, the effect of AFO on gait parameters in post-stroke patients according to the Brunnstrom stage of stroke recovery of the lower limbs remains unclear. The study aimed to investigate whether stroke patients with different Brunnstrom stages benefit from wearing AFO.

METHODS

Twenty-five post-stroke participants included 18 men (50 ± 13 years) and 7 women (60 ± 15 years). The patients were divided based on Brunnstrom stage III or IV of the lower limbs. All patients underwent the gait and timed up and go (TUG) test using a gait analysis system while walking barefoot or with an AFO. The spatiotemporal and asymmetric parameters were analyzed.

RESULTS

All 25 patients completed the study. Significant differences were observed between barefoot and AFO use in TUG time (P < 0.001) but not walking velocity (P > 0.05). The main effect of the swing time ratio was significant in both groups (P < 0.05); however, the main effects of stride length, stance time, and gait asymmetry ratio were nonsignificant (P > 0.05). For barefoot versus AFO, the main effects of stride length (P < 0.05) and swing time (P < 0.01) ratios were significant, whereas those of stance time and gait asymmetry ratio were nonsignificant (P > 0.05).

CONCLUSIONS

Post-stroke patients with lower Brunnstrom stages benefitted more from AFO, particularly in gait asymmetry.

Gait metrics analysis utilizing single-point inertial measurement units: a systematic review

BACKGROUND

Wearable sensors, particularly accelerometers alone or combined with gyroscopes and magnetometers in an inertial measurement unit (IMU), are a logical alternative for gait analysis. While issues with intrusive and complex sensor placement limit practicality of multi-point IMU systems, single-point IMUs could potentially maximize patient compliance and allow inconspicuous monitoring in daily-living. Therefore, this review aimed to examine the validity of single-point IMUs for gait metrics analysis and identify studies employing them for clinical applications.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) were followed utilizing the following databases: PubMed; MEDLINE; EMBASE and Cochrane. Four databases were systematically searched to obtain relevant journal articles focusing on the measurement of gait metrics using single-point IMU sensors.

RESULTS

A total of 90 articles were selected for inclusion. Critical analysis of studies was conducted, and data collected included: sensor type(s); sensor placement; study aim(s); study conclusion(s); gait metrics and methods; and clinical application. Validation research primarily focuses on lower trunk sensors in healthy cohorts. Clinical applications focus on diagnosis and severity assessment, rehabilitation and intervention efficacy and delineating pathological subjects from healthy controls.

DISCUSSION

This review has demonstrated the validity of single-point IMUs for gait metrics analysis and their ability to assist in clinical scenarios. Further validation for continuous monitoring in daily living scenarios and performance in pathological cohorts is required before commercial and clinical uptake can be expected.

A gait abnormality measure based on root mean square of trunk acceleration

Background

Root mean square (RMS) of trunk acceleration is seen frequently in gait analysis research. However, many studies have reported that the RMS value was related to walking speed. Therefore, the relationship between the RMS value and walking speed should be considered when the RMS value is used to assess gait abnormality. We hypothesized that the RMS values in three sensing axes exhibit common proportions for healthy people if they walk at their own preferred speed and that the RMS proportions in abnormal gait deviate from the common proportions. In this study, we proposed the RMS ratio (RMSR) as a gait abnormality measure and verified its ability to discriminate abnormal gait.

Methods

Forty-seven healthy male subjects (24–49 years) were recruited to examine the relationship between walking speed and the RMSR. To verify its ability to discriminate abnormal gait, twenty age-matched male hemiplegic patients (30–48 years) participated as typical subjects with gait abnormality. A tri-axial accelerometer was attached to their lower back, and they walked along a corridor at their own preferred speed. We defined the RMSR as the ratio between RMS in each direction and the RMS vector magnitude.

Results

In the healthy subjects, the RMS in all directions related to preferred walking speed. In contrast, RMSR in the mediolateral (ML) direction did not correlate with preferred walking speed (rs = -0.10, p = 0.54) and represented the similar value among the healthy subjects. Moreover, the RMSR in the ML direction for the hemiplegic patients was significantly higher than that for the healthy subjects (p < 0.01).

Conclusions

These results suggest that the RMSR in the ML direction exhibits a common value when healthy subjects walk at their own preferred speed, even if their preferred walking speed were different. For subjects with gait abnormality, the RMSR in the ML direction deviates from the common value of healthy subjects. The RMSR in the ML direction may potentially be a quantitative measure of gait abnormality.

Multi-parametric evaluation of sit-to-stand and stand-to-sit transitions in elderly people

The aim of this study was to extract multi-parametric measures characterizing different features of sit-to-stand (Si-St) and stand-to-sit (St-Si) transitions in older persons, using a single inertial sensor attached to the chest. Investigated parameters were transition's duration, range of trunk tilt, smoothness of transition pattern assessed by its fractal dimension, and trunk movement's dynamic described by local wavelet energy. A measurement protocol with a Si-St followed by a St-Si postural transition was performed by two groups of participants: the first group (N=79) included Frail Elderly subjects admitted to a post-acute rehabilitation facility and the second group (N=27) were healthy community-dwelling elderly persons. Subjects were also evaluated with Tinetti's POMA scale. Compared to Healthy Elderly persons, frail group at baseline had significantly longer Si-St (3.85±1.04 vs. 2.60±0.32, p=0.001) and St-Si (4.08±1.21 vs. 2.81±0.36, p=0.001) transition's duration. Frail older persons also had significantly decreased smoothness of Si-St transition pattern (1.36±0.07 vs. 1.21±0.05, p=0.001) and dynamic of trunk movement. Measurements after three weeks of rehabilitation in frail older persons showed that smoothness of transition pattern had the highest improvement effect size (0.4) and discriminative performance. These results demonstrate the potential interest of such parameters to distinguish older subjects with different functional and health conditions.

Computer-aided analysis of gait rhythm fluctuations in amyotrophic lateral sclerosis

Deterioration of motor neurons due to amyotrophic lateral sclerosis (ALS) would affect the strides from one gait cycle to the next. Computer-assisted techniques are useful for gait analysis, and also have high potential in quantitatively monitoring the pathological progression. In this paper, we applied the signal turns count method to measure the fluctuations in the swing-interval time series recorded from 16 healthy control subjects and 13 patients with ALS. The swing-interval turns count (SWITC) parameter derived with the threshold of 0.06 s presented a significant difference (p < 0.001) between the healthy control subjects and ALS patients. Besides the SWITC, we also computed the averaged stride interval (ASI), which is usually longer in the patient with ALS (p < 0.0001), to characterize the gait patterns of ALS patients. In the pattern classification experiments, the Fisher's linear discriminant analysis (FLDA) and the least squares support vector machine (LS-SVM), both input with the SWITC and ASI features, were evaluated using the leave-one-out cross-validation method. The results showed that the LS-SVM with sigmoid kernels was able to provide a classification accurate rate of 89.66% and an area of 0.9629 under the receiver operating characteristic (ROC) curve, which were superior to those obtained with the linear classifier in the form of FLDA.

Analysis of stroke patient walking dynamics using a tri-axial accelerometer

The purpose of this study was to describe the characteristics of stroke patient gait using the acceleration signals which were obtained during walking. Sixty-three stroke hemiplegic patients and 21 age-matched healthy elderly individuals took part in this study. A wireless tri-axial accelerometer, fixed to a belt at the level of the L3 spinous process, was used to measure trunk acceleration. Subjects were instructed to walk at a self-selected, comfortable walking speed. The acceleration signal was sampled at the rate of 200 Hz. Gait parameters and functional recovery tests were also evaluated. We analyzed the correlation between the gait parameters, functional recovery and acceleration. Acceleration was utilized as the root mean square (RMS), normalized RMS by velocity and average step length, as a measure of gait smoothness, and autocorrelation (AC) as a measure of stride similarity and regularity. The raw RMS and AC values of the stroke were significantly lower than the matched healthy elderly (p<0.01) in all axes. In contrast, the stroke patients' normalized RMS values were higher than the controls (p<0.05) in all axes. These results suggest that accelerometry gait parameters can discriminate between the stroke patients and the control group. The values of normalized RMS correlated with the smoothness or dynamics of the walking pattern, which reflects motor recovery and gait abilities. This study suggests that normalized RMS of accelerometer recordings from the trunk is valid in objectively measuring walking movements as an index of treatment outcome for patients in rehabilitation.

Lower trunk motion and speed-dependence during walking

BACKGROUND

There is a limited understanding about how gait speed influences the control of upper body motion during walking. Therefore, the primary purpose of this study was to examine how gait speed influences healthy individual's lower trunk motion during overground walking. The secondary purpose was to assess if Principal Component Analysis (PCA) can be used to gain further insight into postural responses that occur at different walking speeds.

METHODS

Thirteen healthy subjects (23 +/- 3 years) performed 5 straight-line walking trials at self selected slow, preferred, and fast walking speeds. Accelerations of the lower trunk were measured in the anterior-posterior (AP), vertical (VT), and mediolateral (ML) directions using a triaxial accelerometer. Stride-to-stride acceleration amplitude, regularity and repeatability were examined with RMS acceleration, Approximate Entropy and Coefficient of Multiple determination respectively. Coupling between acceleration directions were calculated using Cross Approximate Entropy. PCA was used to reveal the dimensionality of trunk accelerations during walking at slow and preferred speeds, and preferred and fast speeds.

RESULTS

RMS acceleration amplitude increased with gait speed in all directions. ML and VT trunk accelerations had less signal regularity and repeatability during the slow compared to preferred speed. However, stride-to-stride acceleration regularity and repeatability did not differ between the preferred and fast walking speed conditions, partly due to an increase in coupling between frontal plane accelerations. The percentage of variance accounted for by each trunk acceleration Principal Component (PC) did not differ between grouped slow and preferred, and preferred and fast walking speed acceleration data.

CONCLUSION

The main finding of this study was that walking at speeds slower than preferred primarily alters lower trunk accelerations in the frontal plane. Despite greater amplitudes of trunk acceleration at fast speeds, the lack of regularity and repeatability differences between preferred and fast speeds suggest that features of trunk motion are preserved between the same conditions. While PCA indicated that features of trunk motion are preserved between slow and preferred, and preferred and fast speeds, the discriminatory ability of PCA to detect speed-dependent differences in walking patterns is limited compared to measures of signal regularity, repeatability, and coupling.

Accelerometry: a technique for quantifying movement patterns during walking

The popularity of using accelerometer-based systems to quantify human movement patterns has increased in recent years for clinicians and researchers alike. The benefits of using accelerometers compared to more traditional gait analysis instruments include low cost; testing is not restricted to a laboratory environment; accelerometers are small, therefore walking is relatively unrestricted; and direct measurement of 3D accelerations eliminate errors associated with differentiating displacement and velocity data. However, accelerometry is not without its disadvantages, an issue which is scarcely reported in gait analysis literature. This paper reviews the use of accelerometer technology to investigate gait-related movement patterns, and addresses issues of acceleration measurement important for experimental design. An overview of accelerometer mechanics is provided before illustrating specific experimental conditions necessary to ensure the accuracy of gait-related acceleration measurement. A literature review is presented on how accelerometry has been used to examine basic temporospatial gait parameters, shock attenuation, and segmental accelerations of the body during walking. The output of accelerometers attached to the upper body has provided useful insights into the motor control of normal walking, age-related differences in dynamic postural control, and gait patterns in people with movement disorders.

Wearable accelerometer system for measuring the temporal parameters of gait

A small and wireless accelerometer system was developed for the estimation of temporal gait parameters. The new system was built using two 3-axis accelerometers. Measurement's accuracy was assessed using as a criterion standard provided by foot switches. To assess the consistency of this system, estimates of heel contact and toe off time based on accelerometers and those based on footswitches were compared for 20 steps from 8 individual healthy subjects. Accelerometers and footswitches had high consistency in the temporal gait parameters. The stance, swing, single support, and double support time of gait cycle revealed ICCs values of 0.95, 0.93, 0.86, and 0.75 on the right and 0.96, 0.86, 0.93, 0.84 on the left, respectively. Therefore, this system proved to be a reliable tool for identification of temporal gait parameters.