Physical Therapy and Parkinsonʼs Disease: A Controlled Clinical Trial

Parkinson's Disease (PD) being the second most hazardous neurological disorder has developed its roots in damaging people's quality of life (QOL). The ineffectiveness of clinical rating scales makes the PD diagnosis a very complicated task. Thus, more efficient systems are required to perform an automated evaluation of PD for its earlier detection and to enhance life expectancy rate. Gait based clinical diagnosis can provide useful indications regarding the presence of PD. From recent years, computer vision-based (VB) analysis is in great demand and seems to be highly effective in PD inspection. The objective of this article is to systematically analyze the applications of computer vision in PD evaluation through gait. This paper surveys the VB PD gait acquisition modalities as well as provides a concise overview of preprocessing techniques. The study presents a description of PD related gait features, extraction and selection methods used for PD analysis. A number of machine learning techniques for classification of PD and healthy gait are also discussed. This article extensively surveys PD gait datasets considering data from 1997 to 2018. Also, several research gaps in existing studies have identified that need to be addressed in the future. At last, an outline of the proposed idea is given that can cope up with the related issues and can lead to quality VB PD gait investigation.

/pdf/computer-vision-based-diagnosis-of-parkinson-s-disease-via-52cc5iaw8h.pdf

Computer-Vision Based Diagnosis of Parkinson’s Disease via Gait: A Survey

This preliminary study was aimed to present the results of the comparison of clinical and functional outcomes of vertebral body tethering (VBT) and posterior spinal fusion (PSF) for the first time in the literature. 21 thoracolumbar (T5-L3) VBT patients (VBT group); and 22 age–gender–fusion level and minimum follow-up duration matched thoracolumbar (T3-L3) PSF patients (PSF group) were enrolled. Average FU duration of group 1 and 2 were 37.1/37.8 months (p = 0.33). Patients clinical data together with SRS-22 scores and SF-36 scores were compared. A retrospective, comparative study was undertaken. VBT group was detected to have superior lumbar range of motion; superior anterior–lateral lumbar bending flexibility; superior flexor and extensor endurances of trunk, and superior average motor strength of trunk muscles with high statistical significance. VBT group was also detected to have superior scores regarding life quality, including better average total SRS-22 and better average SF-36 MCS/PCS scores with also high statistical significance. This study for the first time in the literature concluded, that in skeletally immature patients with AIS, VBT as a result of the utilization of growth modulation was able to yield significantly superior lumbar range of motion, lumbar anterior and lateral flexibility, trunk flexor–extensor endurance and trunk motor strength as compared to patients who underwent fusion. By yielding significantly superior SRS-22 and SF-36 scores, VBT was detected to provide better life quality and patient satisfaction than fusion. This study concluded hereby, that by applying VBT, spinal motion could be preserved and complications of fusion could be avoided.

Comparison of clinical and functional outcomes of vertebral body tethering to posterior spinal fusion in patients with adolescent idiopathic scoliosis and evaluation of quality of life: preliminary results

Abstract Objective: Electroencephalography (EEG) has an influential role in neuroscience and commercial applications. Most of the tools available for EEG signal analysis use machine learning to extract the required information. So, the study of robust techniques for feature extraction and classification is an important thing to understand the practical use of EEG. The paper aims that if there is any special tool for a particular task. Which feature domain or classifier has a significant role in EEG signal analysis? Approach: It presents a detailed report of the current trend for bio-electrical signals classification focusing on various classifiers’ advantages and disadvantages. This study includes literature from 2000 to 2021 with a brief description of EEG signal origin and advancement in classification techniques. Results: Randomly used classifiers for EEG signal can be categorized into five classes, namely Linear Classifiers, Nearest Neighbor Classifiers, Nonlinear Bayesian Classifiers, Neural Networks, and Combinations of Classifiers. Approximately 40% of studies use Support Vector Machine, Nearest Neighbor, and their combination with others. For specific tasks, particular classifiers are recommended in the survey. Features can be defined into four categories, namely TDFs, FDFs, TFDFs, and statistical features, where 39% of studies used TFDFs. Multi-domains features are preferred when the required information cannot be obtained from one domain. Significance: The paper summarizes the recent approaches for feature extraction and classification of EEG signals. It describes the brain waves with their classification, related behavior, and task with the physiological correlation. The comparative analysis of different classifiers, toolbox, the channel used, accuracy, and the number of subjects from various studies can help the practitioners choose a suitable classifier. Furthermore, future directions can cope up with the relevant problems and can lead to accurate classification.

Recent Approaches on Classification and Feature Extraction of EEG Signal: A Review

[Purpose] The aim of this study was to explore the effects of different frequencies of rhythmic auditory cueing (RAC) on stride length, cadence, and gait speed in healthy young females. The findings of this study might be used as clinical guidance of physical therapy for choosing the suitable frequency of RAC. [Subjects] Thirteen healthy young females were recruited in this study. [Methods] Ten meters walking tests were measured in all subjects under 4 conditions with each repeated 3 times and a 3-min seated rest period between repetitions. Subjects first walked as usual and then were asked to listen carefully to the rhythm of a metronome and walk with 3 kinds of RAC (90%, 100%, and 110% of the mean cadence). The three frequencies (90%, 100%, and 110%) of RAC were randomly assigned. Gait speed, stride length, and cadence were calculated, and a statistical analysis was performed using the SPSS (version 17.0) computer package. [Results] The gait speed and cadence of 90% RAC walking showed significant decreases compared with normal walking and 100% and 110% RAC walking. The stride length, cadence, and gait speed of 110% RAC walking showed significant increases compared with normal walking and 90% and 100% RAC walking. [Conclusion] Our results showed that 110% RAC was the best of the 3 cueing frequencies for improvement of stride length, cadence, and gait speed in healthy young females.

Effects of different frequencies of rhythmic auditory cueing on the stride length, cadence, and gait speed in healthy young females.

Augmented Feedback Using Visual Cues for Movement Smoothness during Gait Performance of Individuals with Parkinson's Disease

/pdf/incorrect-use-of-proprioceptive-neuromuscular-facilitation-1j3dn76wrw.pdf

Incorrect use of proprioceptive neuromuscular facilitation-techniques and principles, a response to: Proprioceptive neuromuscular facilitation training improves pain-related and balance outcomes in working-age patients with chronic low back pain: a randomized controlled trial.

The purpose of this study was to compare the static balance in a sitting position between a group with adolescent idiopathic scoliosis (AIS) and a normal aged-matched group. Forty-nine subjects were included in this study. Thirty-one healthy subjects and eighteen AIS subjects were participated. Each group was tested with the Lumbar Trunk Muscle Endurance Test (LTMET) and Balance Performance Monitor (BPM). The parameters for static balance were sway area, sway path, mean balance, maximum velocity, anterior-posterior angle, and left-right angle of each group with eyes opened and closed. Results from the LTMET showed significantly more increase in the normal group than in the AIS group in the flexor and extensor endurance. The BPM tested showed significantly difference beteen the groups in parameters of sitting balance such as maximum velocity and anterior-posterior sway angle. For the AIS subjects, there were no significant differences in all parameters of sitting balance between eyes opened and eyes closed. In comparisons of the groups with eyes opened there were no significant differences in all parameters of sitting balance. In comparisons of the groups with eyes closed there were significant differences in the sway area, maximum velocity, anterior-posterior sway angle and left-right sway angle. These results suggest that the AIS group relies much more on proprioception than on vision, and develops compensatory passive postures of the spine. Further study is needed to measure many AIS patients with morphologic and electromyographic data for clinical application.

Characteristics of Sitting Balance and Trunk Muscle Endurance in Patients With Adolescent Idiopathic Scoliosis

The purpose of this study was to compare spatio-temporal parameters during walking between patients with idiopathic Parkinson's disease and a control group matched for age, height, and weight. Thirty-three subjects were included in this study. Fifteen normal subjects (age, yrs; height, cm; weight, kg) and eighteen patients (age, yrs; height, cm; weight, kg) participated in the study. The Vicon 512 Motion analysis system was used for gait analysis in each group during walking, with and without an obstacle. The measured spatio-temporal parameters were cadence, walking speed, stride time, step time, single limb support time, double limb support time, stride length, and step length. Results in stride length and step length, when walking without an obstacle, showed a significantly greater decrease in the patient group compared to the control group. During walking with an obstacle, the patient group showed a significantly greater decrease in the step length as compared to the control group. For the control group, there were significant decreases in parameters of cadence and walking speed and increases in parameters of stride time, step time, and single limb support time when walking with an obstacle. The patient group had lower cadence and walking speed and higher stride time, step time, and single limb support time during walking with an obstacle than in walking without an obstacle. These results suggest that patients with Parkinson's disease who walk over an obstacle can decrease cadence, stride length, and step length. Further study is needed, performed with more obstacles and combined with other external cues, such as visual or acoustic guides.

Seung-Sub Shin

Papers

Augmented Feedback Using Visual Cues for Movement Smoothness during Gait Performance of Individuals with Parkinson's Disease

Incorrect use of proprioceptive neuromuscular facilitation-techniques and principles, a response to: Proprioceptive neuromuscular facilitation training improves pain-related and balance outcomes in working-age patients with chronic low back pain: a randomized controlled trial.

Characteristics of Sitting Balance and Trunk Muscle Endurance in Patients With Adolescent Idiopathic Scoliosis

Characteristics of Spatio-Temporal Parameters in Parkinson's Disese During Walking