Recent Trends and Practices Toward Assessment and Rehabilitation of Neurodegenerative Disorders: Insights From Human Gait

Diagnosis of neurodegenerative diseases with a refined Lempel-Ziv complexity

The investigation into the distinctive difference of gait is of significance for the clinical diagnosis of neurodegenerative diseases. However, human gait is affected by many factors like behavior, occupation and so on, and they may confuse the gait differences among Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. For the purpose of examining distinctive gait differences of neurodegenerative diseases, this study extracts various features from both vertical ground reaction force and time intervals. Moreover, refined Lempel-Ziv complexity is proposed considering the detailed distribution of signals based on the median and quartiles. Basic features (mean, coefficient of variance, and the asymmetry index), nonlinear dynamic features (Hurst exponent, correlation dimension, largest Lyapunov exponent), and refined Lempel-Ziv complexity of different neurodegenerative diseases are compared statistically by violin plot and Kruskal-Wallis test to reveal distinction and regularities. The comparative analysis results illustrate the gait differences across these neurodegenerative diseases by basic features and nonlinear dynamic features. Classification results by random forest indicate that the refined Lempel-Ziv complexity can robustly enhance the diagnosis accuracy when combined with basic features.

A biomechanical analysis of turning during gait in individuals with different subtypes of Parkinson's disease

BACKGROUND

Turning while walking is a complex component of locomotor capacity, which can be challenging in the daily lives of people with Parkinson's disease. The aim of the study was to compare biomechanical strategies during turning of gait in individuals with Parkinson's disease and its different clinical subtypes.

METHODS

A cross-sectional study, comprising of 43 individuals with idiopathic Parkinson's disease, divided in subgroups: akineto-rigid, dominant tremor and mixed. Motor impairment was assessed using the Unified Parkinson's Disease Rating Scale. The gait biomechanical parameters (number of steps, step length, cadence, amplitude, velocity and radius of the turn) were analyzed during turning in a kinematics laboratory. In the statistical analysis, a comparison was made between subgroups, and correlations between biomechanical parameters.

FINDINGS

There was no statistically significant difference between the subgroups. In the correlation analysis, notable correlations were found between the anticipatory step length and the following variables: number of steps (r = -0.418), step length while turning (r = 0.805), step length after turning (r = 0.644), average velocity (r = 0.830), average velocity while turning (r = 0.755), and maximum velocity (rho = 0.835).

INTERPRETATION

The difficulties primarily occur during the anticipatory phase of the turn, which affects the entire task. The greater the length of the anticipatory step, the greater the length of the step taken to turn as well as the step taken after turning. And the greater the velocity, the greater the step length, and to fewer steps taken to perform the task.

Topical Cellular/Tissue and Molecular Aspects Regarding Nonpharmacological Interventions in Alzheimer's Disease-A Systematic Review

One of the most complex and challenging developments at the beginning of the third millennium is the alarming increase in demographic aging, mainly-but not exclusively-affecting developed countries. This reality results in one of the harsh medical, social, and economic consequences: the continuously increasing number of people with dementia, including Alzheimer's disease (AD), which accounts for up to 80% of all such types of pathology. Its large and progressive disabling potential, which eventually leads to death, therefore represents an important public health matter, especially because there is no known cure for this disease. Consequently, periodic reappraisals of different therapeutic possibilities are necessary. For this purpose, we conducted this systematic literature review investigating nonpharmacological interventions for AD, including their currently known cellular and molecular action bases. This endeavor was based on the PRISMA method, by which we selected 116 eligible articles published during the last year. Because of the unfortunate lack of effective treatments for AD, it is necessary to enhance efforts toward identifying and improving various therapeutic and rehabilitative approaches, as well as related prophylactic measures.

Wearable multisource quantitative gait analysis of Parkinson's diseases

As the motor symptoms of Parkinson's disease (PD) are complex and influenced by many factors, it is challenging to quantify gait abnormalities adequately using a single type of signal. Therefore, a wearable multisource gait monitoring system is developed to perform a quantitative analysis of gait abnormalities for improving the effectiveness of the clinical diagnosis. To detect multisource gait data for an accurate evaluation of gait abnormalities, force sensitive sensors, piezoelectric sensors, and inertial measurement units are integrated into the devised device. The modulation circuits and wireless framework are designed to simultaneously collect plantar pressure, dynamic deformation, and postural angle of the foot and then wirelessly transmit these collected data. With the designed system, multisource gait data from PD patients and healthy controls are collected. Multisource features for quantifying gait abnormalities are extracted and evaluated by a significance test of difference and correlation analysis. The results show that the features extracted from every single type of data are able to quantify the health status of the subjects (p < 0.001, ρ > 0.50). More importantly, the validity of multisource gait data is verified. The results demonstrate that the gait feature fusing multisource data achieves a maximum correlation coefficient of 0.831, a maximum Area Under Curve of 0.9206, and a maximum feature-based classification accuracy of 88.3%. The system proposed in this study can be applied to the gait analysis and objective evaluation of PD.

Telehealth-based exercise in amyotrophic lateral sclerosis

The Veterans Health Administration (VHA) has served as a leader in the implementation of telerehabilitation technologies and continues to expand utilization of non-traditional patient encounters to better serve a geographically and demographically diverse population. Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease impacting Veterans at a higher rate than the civilian population and associated with high levels of disability and limited access to subspecialized care. There is growing evidence supporting exercise-based interventions as an independent or adjunctive treatment to maintain or restore function for this patient population; many of these interventions can be delivered remotely by telehealth. The recent advancements in disease-modifying therapies for neuromuscular disorders will likely increase the importance of rehabilitation interventions to maximize functional outcomes. Here, we review the evidence for specific exercise interventions in ALS and the evidence for telehealth-based exercise in neuromuscular disorders. We then use this existing literature to propose a framework for telehealth delivery of these treatments, including feasible exercise interventions and remote outcome measures, recommended peripheral devices, and an example of a current remote group exercise program offered through VHA.

Gait Analysis in Neurorehabilitation: From Research to Clinical Practice

When brain damage occurs, gait and balance are often impaired. Evaluation of the gait cycle, therefore, has a pivotal role during the rehabilitation path of subjects who suffer from neurological disorders. Gait analysis can be performed through laboratory systems, non-wearable sensors (NWS), and/or wearable sensors (WS). Using these tools, physiotherapists and neurologists have more objective measures of motion function and can plan tailored and specific gait and balance training early to achieve better outcomes and improve patients' quality of life. However, most of these innovative tools are used for research purposes (especially the laboratory systems and NWS), although they deserve more attention in the rehabilitation field, considering their potential in improving clinical practice. In this narrative review, we aimed to summarize the most used gait analysis systems in neurological patients, shedding some light on their clinical value and implications for neurorehabilitation practice.

Effects of age, body height, body weight, body mass index and handgrip strength on the trajectory of the plantar pressure stance-phase curve of the gait cycle

The analysis of gait patterns and plantar pressure distributions via insoles is increasingly used to monitor patients and treatment progress, such as recovery after surgeries. Despite the popularity of pedography, also known as baropodography, characteristic effects of anthropometric and other individual parameters on the trajectory of the stance phase curve of the gait cycle have not been previously reported. We hypothesized characteristic changes of age, body height, body weight, body mass index and handgrip strength on the plantar pressure curve trajectory during gait in healthy participants. Thirty-seven healthy women and men with an average age of 43.65 ± 17.59 years were fitted with Moticon OpenGO insoles equipped with 16 pressure sensors each. Data were recorded at a frequency of 100 Hz during walking at 4 km/h on a level treadmill for 1 minute. Data were processed via a custom-made step detection algorithm. The loading and unloading slopes as well as force extrema-based parameters were computed and characteristic correlations with the targeted parameters were identified via multiple linear regression analysis. Age showed a negative correlation with the mean loading slope. Body height correlated with Fmean_load and the loading slope. Body weight and the body mass index correlated with all analyzed parameters, except the loading slope. In addition, handgrip strength correlated with changes in the second half of the stance phase and did not affect the first half, which is likely due to stronger kick-off. However, only up to 46% of the variability can be explained by age, body weight, height, body mass index and hand grip strength. Thus, further factors must affect the trajectory of the gait cycle curve that were not considered in the present analysis. In conclusion, all analyzed measures affect the trajectory of the stance phase curve. When analyzing insole data, it might be useful to correct for the factors that were identified by using the regression coefficients presented in this paper.