Prevalence of distinct types of hardware failures related to deep brain stimulation.

Deep brain stimulation (DBS) is an effective treatment of several types of neurological conditions, including Parkinson's disease, essential tremor, dystonia, and epilepsy. Despite technological progress in the past 10 years, the number of studies reporting side effects of DBS has increased, mainly due to hardware failures. This review investigated studies published between 2017 and 2021 to identify the prevalence of distinct types of hardware failures related to DBS. In total, fifteen studies were selected for the estimate of the prevalence of five distinct types of hardware failures: high impedance, fracture or failure of the lead or other parts of the implant, skin erosion and infection, lead malposition or migration, and implantable pulse generator (IPG) malfunction. The quality evaluation of the studies suggests a need to report results including populations from distinct regions of the world so that results can be generalized. The objective analysis of the prevalence of hardware failures showed that skin erosion and infection presented the highest prevalence in relation to other hardware failures. Despite the sophistication of the surgical technique of DBS over time, there is a considerable complication rate, about 7 per 100 individuals ([Formula: see text], in which CI is the confidence interval). Future research can also include correlation analysis with the aim of understanding the correlation between distinct hardware failures and variables such as gender, type of disorder, and age.

Discrimination between healthy and patients with Parkinson's disease from hand resting activity using inertial measurement unit.

BACKGROUND: Parkinson's disease (PD) is a neurological disease that affects the motor system. The associated motor symptoms are muscle rigidity or stiffness, bradykinesia, tremors, and gait disturbances. The correct diagnosis, especially in the initial stages, is fundamental to the life quality of the individual with PD. However, the methods used for diagnosis of PD are still based on subjective criteria. As a result, the objective of this study is the proposal of a method for the discrimination of individuals with PD (in the initial stages of the disease) from healthy groups, based on the inertial sensor recordings. METHODS: A total of 27 participants were selected, 15 individuals previously diagnosed with PD and 12 healthy individuals. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Different numbers of features were used to compare the values of sensitivity, specificity, precision, and accuracy of the classifiers. For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)]. RESULTS: When all individuals with PD were analyzed, the best performance for sensitivity and accuracy (0.875 and 0.800, respectively) was found in the SVM classifier, fed with 20% and 10% of the features, respectively, while the best performance for specificity and precision (0.933 and 0.917, respectively) was associated with the RF classifier fed with 20% of all the features. When only individuals with PD and score 1 on the Hoehn and Yahr scale (HY) were analyzed, the best performances for sensitivity, precision and accuracy (0.933, 0.778 and 0.848, respectively) were from the SVM classifier, fed with 40% of all features, and the best result for precision (0.800) was connected to the NB classifier, fed with 20% of all features. CONCLUSION: Through an analysis of all individuals in this study with PD, the best classifier for the detection of PD (sensitivity) was the SVM fed with 20% of the features and the best classifier for ruling out PD (specificity) was the RF classifier fed with 20% of the features. When analyzing individuals with PD and score HY = 1, the SVM classifier was superior across the sensitivity, precision, and accuracy, and the NB classifier was superior in the specificity. The obtained result indicates that objective methods can be applied to help in the evaluation of PD.

Identification of arthropathy and myopathy of the temporomandibular syndrome by biomechanical facial features.

BACKGROUND: Temporomandibular disorders (TMDs) are pathological conditions affecting the temporomandibular joint and/or masticatory muscles. The current diagnosis of TMDs is complex and multi-factorial, including questionnaires, medical testing and the use of diagnostic methods, such as computed tomography and magnetic resonance imaging. The evaluation, like the mandibular range of motion, needs the experience of the professional in the field and as such, there is a probability of human error when diagnosing TMD. The aim of this study is therefore to develop a method with infrared cameras, using the maximum range of motion of the jaw and four types of classifiers to help professionals to classify the pathologies of the temporomandibular joint (TMJ) and related muscles in a quantitative way, thus helping to diagnose and follow up on TMD. METHODS: Forty individuals were evaluated and diagnosed using the diagnostic criteria for temporomandibular disorders (DC/TMD) scale, and divided into three groups: 20 healthy individuals (control group CG), 10 individuals with myopathies (MG), 10 individuals with arthropathies (AG). A quantitative assessment was carried out by motion capture. The TMJ movement was captured with camera tracking markers mounted on the face and jaw of each individual. Data was exported and analyzed using a custom-made software. The data was used to identify and place each participant into one of three classes using the K-nearest neighbor (KNN), Random Forest, Naïve Bayes and Support Vector Machine algorithms. RESULTS: Significant precision and accuracy (over 90%) was reached by KNN when classifying the three groups. The other methods tested presented lower values of sensitivity and specificity. CONCLUSION: The quantitative TMD classification method proposed herein has significant precision and accuracy over the DC/TMD standards. However, this should not be used as a standalone tool but as an auxiliary method for diagnostic TMDs.

Effects of backpack load and positioning on nonlinear gait features in young adults.

Overloaded backpacks can cause changes in posture and gait dynamic balance. Therefore, the aim of this study was to assess gait regularity and local dynamic stability in young adults as they carried a backpack in different positions, and with different loads. Twenty-one healthy young adults participated in the study, carrying a backpack that was loaded with 10 and 20% of their body weight (BW). The participants walked on a level treadmill at their preferred walking speeds for 4 min under different conditions of backpack load and position (i.e. with backpack positioned back bilaterally, back unilaterally, frontally or without a backpack). Results indicate that backpack load and positioning significantly influence gait stability and regularity, with the exception of the 10% BW bilateral back position. Therefore, the recommended safe load for school-age children and adolescents (10% of BW) should also be considered for young adults. Practitioner summary: Increase in load results in changes in posture, muscle activity and gait parameters, so we investigated the gait adaptations related to regularity and stability. Conditions with high backpack loads significantly influenced gait stability and regularity in a position-dependent manner, except for 10% body weight bilateral back position.

Feature visualization and classification for the discrimination between individuals with Parkinson's disease under levodopa and DBS treatments.

BACKGROUND: Over the years, a number of distinct treatments have been adopted for the management of the motor symptoms of Parkinson's disease (PD), including pharmacologic therapies and deep brain stimulation (DBS). Efficacy is most often evaluated by subjective assessments, which are prone to error and dependent on the experience of the examiner. Our goal was to identify an objective means of assessing response to therapy. METHODS: In this study, we employed objective analyses in order to visualize and identify differences between three groups: healthy control (N = 10), subjects with PD treated with DBS (N = 12), and subjects with PD treated with levodopa (N = 16). Subjects were assessed during execution of three dynamic tasks (finger taps, finger to nose, supination and pronation) and a static task (extended arm with no active movement). Measurements were acquired with two pairs of inertial and electromyographic sensors. Feature extraction was applied to estimate the relevant information from the data after which the high-dimensional feature space was reduced to a two-dimensional space using the nonlinear Sammon's map. Non-parametric analysis of variance was employed for the verification of relevant statistical differences among the groups (p < 0.05). In addition, K-fold cross-validation for discriminant analysis based on Gaussian Finite Mixture Modeling was employed for data classification. RESULTS: The results showed visual and statistical differences for all groups and conditions (i.e., static and dynamic tasks). The employed methods were successful for the discrimination of the groups. Classification accuracy was 81 ± 6% (mean ± standard deviation) and 71 ± 8%, for training and test groups respectively. CONCLUSIONS: This research showed the discrimination between healthy and diseased groups conditions. The methods were also able to discriminate individuals with PD treated with DBS and levodopa. These methods enable objective characterization and visualization of features extracted from inertial and electromyographic sensors for different groups.

Trunk variability and local dynamic stability during gait after generalized fatigue induced by incremental exercise test in young women in different phases of the menstrual cycle.

Purpose: The purpose of this study was to identify how generalized fatigue along with hormonal changes throughout the menstrual cycle affects trunk variability and local dynamic stability during gait. Methods: General fatigue was induced by an incremental test on a treadmill, and the menstrual cycle was divided into three phases: follicular, ovulatory, and luteal. Twenty-six healthy, young volunteers (aged 18 to 28 years) who did not use oral contraceptives or other hormonal drugs with a regular menstrual cycle participated in the study. They walked on the treadmill for 4 min at the preferred speed, before the incremental test, followed by four sets of 4 min alternating between walking, also at preferred speed, and resting. From trunk kinematic data, the following were extracted: the mean of the standard deviation along strides, as a measure of variability, and the maximum Lyapunov exponent, as a measure of local dynamic stability (LDS). Results: After the incremental test, variability increased, and LDS decreased. However, they showed a tendency to return to the initial value faster in women compared to previous results for men. In the follicular phase, which has less hormonal release, the volunteers had an almost complete recovery in LDS soon after the first rest interval, suggesting that female hormones can interfere with fatigue recovery. Nevertheless, concerning the LDS, it was significantly lower in the luteal phase than in the follicular phase. Conclusion: Women that are not taking oral contraceptives should be aware that they are susceptible to increased gait instabilities in the pre-menstrual phase after strenuous activities.

Vertical stiffness and lower limb inter-joint coordination in older versus younger runners.

Older runners (OR) are increasing their participation in races. Aging may impact the adopted running pattern. Hence, the analysis of stiffness and the inter-joint lower limb coordination in the sagittal plane could contribute to investigating this impact. This study aimed to compare the vertical stiffness (Kvert) and the inter-joint lower limb coordination in the sagittal plane between younger runners (YR) and OR. This cross-sectional study recruited 15 YR males and 15 OR males. The pelvis and lower limb motions were assessed while running on a treadmill at self-selected (range OR: 1.94-3.75 m.s-1, YR: 2.08-4.17 m.s-1) and fixed speeds (3.33 m.s-1). Hip-ankle, knee-ankle, and hip-knee coupling angle (CA) and its variability (CAV) were extracted using the vector coding method. Mann-Whitney U tests compared Kvert between groups at each running speed. Watson's U2 tests compared the mean CA between groups in three intervals of the contact phase at each running speed. Statistical Parametric Mapping independent t-test compared the CAV curve between groups at each running speed. OR showed greater Kvert than YR at both speeds. Hip-ankle CA pattern differed between groups during the early stance at both speed conditions. OR showed in-phase, distal dominancy in hip-ankle CA, whereas YR showed anti-phase, proximal dominancy. Knee-ankle CA was distinct only at self-selected speed, in which OR showed in-phase, proximal dominancy, while YR exhibited anti-phase, proximal dominancy. CAV did not differ between groups. The findings showed that OR adopted a stiffer pattern characterized by distinct inter-joint lower limb CA, at early stance, during self-selected and fixed speeds.

Identification and Characterization of Short-Term Motor Patterns in Rest Tremor of Individuals with Parkinson's Disease.

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson's disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included healthy (N = 12, 60.1 ± 5.9 years old) and PD (N = 14, 65 ± 11.54 years old) participants. The signals were collected using a triaxial gyroscope on the dorsal side of the hand during a resting condition. Data were preprocessed and seven features were extracted from each 1 s window with 50% overlap. The STMPs were identified using the clustering technique k-means applied to the data in the two-dimensional space given by t-Distributed Stochastic Neighbor Embedding (t-SNE). The frequency, transition probability, and duration of the STMPs for each group were assessed. All STMP features were averaged across groups. (3) Results: Three STMPs were identified in tremor signals (p < 0.05). STMP 1 was prevalent in the healthy control (HC) subjects, STMP 2 in both groups, and STMP3 in PD. Only the coefficient of variation and complexity differed significantly between groups. (4) Conclusion: These results can help professionals characterize and evaluate tremor severity and treatment efficacy.

Lower limb inter-joint coordination patterns are associated with walking experience in toddlers according to limb and stance periods.

Walking experience is crucial for inter-joint coordination during gait acquisition. Toddlers show asymmetrical lower limb function during early locomotion for transferring body weight (regulatory limb) and steering the direction of walking (impulse limb). This study aimed to investigate the association between coordination patterns and walking experience, and between coordination variability and walking experience according to healthy toddlers' lower limb function and stance periods. Typically developing toddlers (n = 22; 17.27 ± 3.13 months) were distributed into two groups: up to (LWE) and greater than (GWE) three months of walking experience. The lower limbs were classified as regulatory or impulse limb and analyzed during the onset (SO), mid (MS), and late (LS) stance intervals. Hip-ankle, knee-ankle, and hip-knee coupling angle (CA) and its variability (CAV) were assessed. A relationship was found between inter-joint coordination pattern and groups, which was distinct according to stance period and lower limb function: (a) hip-ankle CA: at SO for both limbs, MS for the regulatory limb, and LS for the impulse limb; (b) knee-ankle CA: at SO for both limbs and MS for the regulatory limb; (c) hip-knee CA: at SO for both limbs, at MS for the regulatory limb, and LS for the impulse limb. These findings were linked to differences observed in distal joints between groups, mainly at the ankle during stance onset. The CAV was negatively associated with walking experience only in the regulatory limb in the following variables: hip-ankle at MS, knee-ankle at SO, and hip-knee at LS. Findings showed different functional roles of the lower limbs in dealing with the demands of balance and propulsion during early walking.

Single channel approach for filtering electroencephalographic signals strongly contaminated with facial electromyography.

Eliminating facial electromyographic (EMG) signal from the electroencephalogram (EEG) is crucial for the accuracy of applications such as brain computer interfaces (BCIs) and brain functionality measurement. Facial electromyography typically corrupts the electroencephalogram. Although it is possible to find in the literature a number of multi-channel approaches for filtering corrupted EEG, studies employing single-channel approaches are scarce. In this context, this study proposed a single-channel method for attenuating facial EMG noise from contaminated EEG. The architecture of the method allows for the evaluation and incorporation of multiple decomposition and adaptive filtering techniques. The decomposition method was responsible for generating EEG or EMG reference signals for the adaptive filtering stage. In this study, the decomposition techniques CiSSA, EMD, EEMD, EMD-PCA, SSA, and Wavelet were evaluated. The adaptive filtering methods RLS, Wiener, LMS, and NLMS were investigated. A time and frequency domain set of features were estimated from experimental signals to evaluate the performance of the single channel method. This set of characteristics permitted the characterization of the contamination of distinct facial muscles, namely Masseter, Frontalis, Zygomatic, Orbicularis Oris, and Orbicularis Oculi. Data were collected from ten healthy subjects executing an experimental protocol that introduced the necessary variability to evaluate the filtering performance. The largest level of contamination was produced by the Masseter muscle, as determined by statistical analysis of the set of features and visualization of topological maps. Regarding the decomposition method, the SSA method allowed for the generation of more suitable reference signals, whereas the RLS and NLMS methods were more suitable when the reference signal was derived from the EEG. In addition, the LMS and RLS methods were more appropriate when the reference signal was the EMG. This study has a number of practical implications, including the use of filtering techniques to reduce EEG contamination caused by the activation of facial muscles required by distinct types of studies. All the developed code, including examples, is available to facilitate a more accurate reproduction and improvement of the results of this study.

Multidimensional Assessment of Individuals with Parkinson's Disease: Development and Structure Validation of a Self-Assessment Questionnaire.

(1) Background: Several instruments are used to assess individuals with Parkinson's disease (PD). However, most instruments necessitate the physical presence of a clinician for evaluation, were not designed for PD, nor validated for remote application. (2) Objectives: To develop and validate a self-assessment questionnaire that can be used remotely, and to assess the respondents' health condition. (3) Methods: A questionnaire, so-called Multidimensional Assessment Questionnaire for Individuals with PD (MAQPD), was developed, administered remotely, and completed by 302 people with PD. MAQPD was validated using factor analysis (FA). The participants' level of impairment was estimated using factor loadings. The scale's accuracy was assessed estimating floor and ceiling effects and Cronbach's alpha. (4) Results: FA suggested classifying the questions into daily activities, cognition, and pain. The respondents did not have extremely severe impairment (most scores ranged from 100 to 180 points), and the factors with the lowest scores were cognition and pain. The instrument had no significant floor or ceiling effects (rates less than 15%), and the Cronbach's alpha value was larger than 0.90. (5) Conclusion: MAQPD is the only remote self-administered tool found in the literature capable of providing a detailed assessment of the general health status of individuals with PD.

Wrist Rigidity Evaluation in Parkinson's Disease: A Scoping Review.

(1) Background: One of the main cardinal signs of Parkinson's disease (PD) is rigidity, whose assessment is important for monitoring the patient's recovery. The wrist is one of the joints most affected by this symptom, which has a great impact on activities of daily living and consequently on quality of life. The assessment of rigidity is traditionally made by clinical scales, which have limitations due to their subjectivity and low intra- and inter-examiner reliability. (2) Objectives: To compile the main methods used to assess wrist rigidity in PD and to study their validity and reliability, a scope review was conducted. (3) Methods: PubMed, IEEE/IET Electronic Library, Web of Science, Scopus, Cochrane, Bireme, Google Scholar and Science Direct databases were used. (4) Results: Twenty-eight studies were included. The studies presented several methods for quantitative assessment of rigidity using instruments such as force and inertial sensors. (5) Conclusions: Such methods present good correlation with clinical scales and are useful for detecting and monitoring rigidity. However, the development of a standard quantitative method for assessing rigidity in clinical practice remains a challenge.

Open-source data management system for Parkinson's disease follow-up.

BACKGROUND: Parkinson's disease (PD) is a neurodegenerative condition of the central nervous system that causes motor and non-motor dysfunctions. The disease affects 1% of the world population over 60 years and remains cureless. Knowledge and monitoring of PD are essential to provide better living conditions for patients. Thus, diagnostic exams and monitoring of the disease can generate a large amount of data from a given patient. This study proposes the development and usability evaluation of an integrated system, which can be used in clinical and research settings to manage biomedical data collected from PD patients. METHODS: A system, so-called Sistema Integrado de Dados Biomédicos (SIDABI) (Integrated Biomedical Data System), was designed following the model-view-controller (MVC) standard. A modularized architecture was created in which all the other modules are connected to a central security module. Thirty-six examiners evaluated the system usability through the System Usability Scale (SUS). The agreement between examiners was measured by Kendall's coefficient with a significance level of 1%. RESULTS: The free and open-source web-based system was implemented using modularized and responsive methods to adapt the system features on multiple platforms. The mean SUS score was 82.99 ± 13.97 points. The overall agreement was 70.2%, as measured by Kendall's coefficient (p < 0.001). CONCLUSION: According to the SUS scores, the developed system has good usability. The system proposed here can help researchers to organize and share information, avoiding data loss and fragmentation. Furthermore, it can help in the follow-up of PD patients, in the training of professionals involved in the treatment of the disorder, and in studies that aim to find hidden correlations in data.

Discrimination capability of linear and nonlinear gait features in group classification.

The variability of human movement can be defined as normal variations occurring in motor activity and quantified using linear statistics or nonlinear methods. In the human movement field, linear and nonlinear measures of variability have been used to discriminate groups and conditions in different contexts. Indeed, some authors support the idea that these gait features provide complementary information about movement. However, it is unclear which type of gait variability measure best discriminates different groups or conditions, as a comparison of the discrimination capacity between linear and nonlinear gait variability features in different groups has not been assessed. Therefore, the main objective of this study was to test the discrimination capacity of linear and nonlinear gait features to determine which type of feature would be the most efficient for discriminating older and younger adults and between lower limb amputees and nonamputees using classification algorithms. Data from previously published studies were used. The classification task was performed using the k-nearest neighbors and random forest algorithms. Our results showed that using a combination of linear and nonlinear features resulted in the highest mean accuracy rates (>90%) in group classification, reinforcing the idea that these features are complementary and express different aspects of movement.

On the use of histograms of oriented gradients for tremor detection from sinusoidal and spiral handwritten drawings of people with Parkinson's disease.

Parkinson's disease (PD), whose cardinal signs are tremor, rigidity, bradykinesia, and postural instability, gradually reduces the quality of life of the patient, making early diagnosis and follow-up of the disorder essential. This study aims to contribute to the objective evaluation of tremor in PD by introducing and assessing histograms of oriented gradients (HOG) to the analysis of handwriting sinusoidal and spiral patterns. These patterns were digitized and collected from handwritten drawings of people with PD (n = 20) and control healthy individuals (n = 20). The HOG descriptor was employed to represent relevant information from the data classified by three distinct machine-learning methods (random forest, k-nearest neighbor, support vector machine) and a deep learning method (convolutional neural network) to identify tremor in participants with PD automatically. The HOG descriptor allowed for the highest discriminating rates (accuracy 83.1%, sensitivity 85.4%, specificity 80.8%, area under the curve 91%) on the test set of sinusoidal patterns by using the one-dimensional convolutional neural network. In addition, ANOVA and Tukey analysis showed that the sinusoidal drawing is more appropriate than the spiral pattern, which is the most common drawing used for tremor detection. This research introduces a novel and alternative way of quantifying and evaluating tremor by means of handwritten drawings.

Effects of additional load at different heights on gait initiation: A statistical parametric mapping of center of pressure and center of mass behavior.

The purpose of this study was to investigate the effects of different vertical positions of an asymmetrical load on the anticipatory postural adjustments phase of gait initiation. Sixty-eight college students (32 males, 36 females; age: 23.65 ± 3.21 years old; weight: 69.98 ± 8.15 kg; height: 1.74 ± 0.08 m) were enrolled in the study. Ground reaction forces and moments were collected using two force platforms. The participants completed three trials under each of the following random conditions: no-load (NL), waist uniformly distributed load (WUD), shoulder uniformly distributed load (SUD), waist stance foot load (WST), shoulder stance foot load (SST), waist swing foot load (WSW), and shoulder swing foot load (SSW). The paired Hotelling's T-square test was used to compare the experimental conditions. The center of pressure (COP) time series were significantly different for the SUD vs. NL, SST vs. NL, WST vs. NL, and WSW vs. NL comparisons. Significant differences in COP time series were observed for all comparisons between waist vs. shoulder conditions. Overall, these differences were greater when the load was positioned at the shoulders. For the center of mass (COM) time series, significant differences were found for the WUD vs. NL and WSW vs. NL conditions. However, no differences were observed with the load positioned at the shoulders. In conclusion, only asymmetrical loading at the waist produced significant differences, and the higher the extra load, the greater the effects on COP behavior. By contrast, only minor changes were observed in COM behavior, suggesting that the changes in COP (the controller) behavior are adjustments to maintain the COM (controlled object) unaltered.

Margins of stability of persons with transtibial or transfemoral amputations walking on sloped surfaces.

Gait is a complex motor skill. However, most falls in humans occur during gait, and people with lower limb amputation have an increased risk of falls. Thus, this study evaluated the stability of persons with unilateral amputation by quantifying the margin of stability (MoS) during gait, to contribute to understanding the strategies adopted by these people to reduce falls. The participants were divided into 3 groups: persons with transtibial amputations (n = 12, 32.27 ± 10.10 years, 76.9 ± 10.3 kg, 1.74 ± 0.06 m); persons with transfemoral amputations (n = 13, 32.21 ± 8.34 years, 72.55 ± 10.23 kg, 1.73 ± 0.05 m); and controls (n = 15, 32.2 ± 10.17 years, 75.4 ± 9.25 kg, 1.75 ± 0.05 m), who walked for 4 min on a level and sloped (8% down and up) treadmill. The pelvic and foot marker kinematic data were used to estimate the center of mass and base of support, and from these, the MoS was estimated. Although both groups of persons with amputations showed higher values for the ML MoS than did the control group (transtibial: 8.81 ± 1.79, 8.97 ± 1.74, 8.79 ± 1.76, transfemoral: 10.15 ± 2.03, 10.60 ± 1.98, 10.11 ± 1.75, control: 8.13 ± 1.30, 7.18 ± 1.85, 8.15 ± 1.57, level, down, and up, respectively), only the transfemoral group presented a significant higher value compared to the control group. Our findings suggest that the documented limitations in persons with amputations, especially with transfemoral amputation, are exacerbated in situations that require more skills, such as walking on sloped surfaces, triggering protective mechanisms.

The effects of general fatigue induced by incremental exercise test and active recovery modes on energy cost, gait variability and stability in male soccer players.

The aerobic endurance is considered an important physiological capacity of soccer players which is examined by Incremental Exercise Test (IET). However, it is not clear how general fatigue induced by IET influences physiological and biomechanical gait features in soccer players and how players recover optimally at post-IET. Here, the effect of general fatigue induced by IET on energy cost, gait variability and stability in soccer players was investigated. To identify an optimal recovery mode, the effect of walking at Preferred Walking Speed (PWS), running at Individual Ventilation Threshold (IVT) (two active recovery modes), and Rest (a passive recovery mode) on aforementioned features were studied. Nine male players walked 4-min at PWS on a treadmill prior IET (PreT), which was followed by four 4-min walking trials (PosT-0, 1, 2, and 3) with three 4-min recovery intervals (PWS, IVT, or Rest) between them, in three sessions (one for each recovery mode) in a random order. Energy cost, gait variability and stability were examined at PreT (baseline), and at PosT-0, 1, 2, and 3 (intervals of respectively 0-4, 8-12, 16-20, 24-28 min at post-IET). Gait variability was assessed by the standard deviation of trunk angle and gait stability was assessed by the local dynamic stability of trunk angular velocity. Gait stability was not affected by IET, despite increases in gait variability and energy cost. Different from IVT, PWS and Rest recovery modes reduced energy cost at post-IET. Gait variability and energy cost recovered at PosT-1 and PosT-2, suggesting that 8-12 and 16-20 min recovery intervals, respectively, were required for returning to their baselines. No preference for active over passive recovery was found in terms of gait variability and energy cost.

A comparison of coordination and its variability in lower extremity segments during treadmill and overground running at different speeds.

BACKGROUND: Recently, the use of treadmills for walking and running has increased due to lifestyle changes. However, biomechanical differences in coordination between running on a treadmill or overground have not been adequately addressed. RESEARCH QUESTION: The purpose of this study was to compare coordination and its variability in lower limb segments during treadmill and overground running at different speeds. METHODS: Twenty physically active university undergraduate students participated in this study. Each participant ran trials for both overground and treadmill running at slow and fast speeds. Three-dimensional kinematic data of the lower limb segments were captured. The continuous relative phase (CRP) was used to compute coordination and its variability (VCRP) for foot, shank, and thigh segments of the dominant side of the participants. RESULTS: A vector analysis using statistical parametric mapping (SPM) revealed that there were statistically significant differences in the calculated CRPs for treadmill and overground running in the stance phase of running and for different running speeds in the late stance and swing phases. However, the VCRPs calculated for the two locations and speeds did not exhibit any statistically significant differences. CONCLUSION: The findings of this study suggest differences in segment coupling between treadmill and overground running may affect lower extremity biomechanics. In addition, changes in the coupling patterns for different running speeds suggest that segment coordination is not stable in the range of training speeds used by runners. Finally, the lack of differences in the variability of segment couplings during treadmill and overground conditions at different speeds potentially demonstrates similar dynamic neuromuscular control and degrees of freedom at these different running locations and speeds.

Effects of triceps surae fatigue and weight training level on gait variability and local stability in young adults.

Muscle fatigue negatively affects gait, and the changes in gait pattern due to muscle fatigue is influenced by which muscles are fatigued and pre-existing physical activity levels. However, how these factors alter gait stability and variability, measures related to risk of fall, remains unclear. To explore how muscular fatigue affects linear and nonlinear gait features in young adults, the effects of triceps surae fatigue and weight training level on gait variability and local stability, as well as a 12-min recovery time of post-fatigue period, were evaluated in young adults (trained and untrained groups). Some features were estimated, i.e., (i) step length (SL) and step frequency (SF), (ii) average standard deviation of trunk acceleration along strides (VAR), and (iii) local dynamic stability (LDS; maximum Lyapunov exponent). LDS presented a significant increase in the anterior-posterior direction with recovery to trained group. SL and SF changed immediately post-fatigue and recovered for both groups, while VAR increased significantly in all directions, with a recovery in the vertical direction for both groups and in the medial-lateral direction for trained group. Localized fatigue affected the analyzed gait variables independent of the participant's training condition, and an interval of 12 min does not seem to be enough for a complete recovery, suggesting a longer recovery period after tasks involving localized triceps surae fatigue to guarantee basal levels of gait variability and local stability. Graphical abstract Flow chart of the experimental protocol. A) Pre-fatigue: 4 min walking at PWS. B) Post-fatigue: first 4 min walking after fatigue protocol. C) Post-fatigue: second 4 min walking after fatigue protocol. D) Post-fatigue: third 4 min walking after fatigue protocol (PWS, preferred walking speed; AP, anterior-posterior; V, vertical; ML, medial-lateral).