Neuromuscular adaptations and sensorimotor integration following a unilateral transfemoral amputation.

BACKGROUND: Following an amputation, the human postural control system develops neuromuscular adaptations to regain an effective postural control. We investigated the compensatory mechanisms behind these adaptations and how sensorimotor integration is affected after a lower-limb transfemoral amputation. METHODS: Center of pressure (CoP) data of 12 unilateral transfemoral amputees and 12 age-matched able-bodied subjects were recorded during quiet standing with eyes open (EO) and closed (EC). CoP adjustments under each leg were recorded to study their contribution to posture control. The spatial structure of the CoP displacements was characterized by measuring the mean distance, the mean velocity of the CoP adjustments, and the sway area. The Entropic Half-Life (EnHL) quantifies the temporal structure of the CoP adjustments and was used to infer disrupted sensory feedback loops in amputees. We expanded the analysis with measures of weight-bearing imbalance and asymmetry, and with two standardized balance assessments, the Berg Balance Scale (BBS) and Timed Up-and-Go (TUG). RESULTS: There was no difference in the EnHL values of amputees and controls when combining the contributions of both limbs (p = 0.754). However, amputees presented significant differences between the EnHL values of the intact and prosthetic limb (p <  0.001). Suppressing vision reduced the EnHL values of the intact (p = 0.001) and both legs (p = 0.028), but not in controls. Vision feedback in amputees also had a significant effect (increase) on the mean CoP distance (p <  0.001), CoP velocity (p <  0.001) and sway area (p = 0.007). Amputees presented an asymmetrical stance. The EnHL values of the intact limb in amputees were positively correlated to the BBS scores (EO: ρ = 0.43, EC: ρ = 0.44) and negatively correlated to the TUG times (EO: ρ = - 0.59, EC: ρ = - 0.69). CONCLUSION: These results suggest that besides the asymmetry in load distribution, there exist neuromuscular adaptations after an amputation, possibly related to the loss of sensory feedback and an altered sensorimotor integration. The EnHL values suggest that the somatosensory system predominates in the control of the intact leg. Further, suppressing the visual system caused instability in amputees, but had a minimal impact on the CoP dynamics of controls. These findings points toward the importance of providing somatosensory feedback in lower-limb prosthesis to reestablish a normal postural control. TRIAL REGISTRATION: DRKS00015254 , registered on September 20th, 2018.

Towards Mobile Gait Analysis: Concurrent Validity and Test-Retest Reliability of an Inertial Measurement System for the Assessment of Spatio-Temporal Gait Parameters.

The purpose of this study was to assess the concurrent validity and test-retest reliability of a sensor-based gait analysis system. Eleven healthy subjects and four Parkinson's disease (PD) patients were asked to complete gait tasks whilst wearing two inertial measurement units at their feet. The extracted spatio-temporal parameters of 1166 strides were compared to those extracted from a reference camera-based motion capture system concerning concurrent validity. Test-retest reliability was assessed for five healthy subjects at three different days in a two week period. The two systems were highly correlated for all gait parameters ( r > 0.93 ). The bias for stride time was 0 ± 16 ms and for stride length was 1.4 ± 6.7 cm. No systematic range dependent errors were observed and no significant changes existed between healthy subjects and PD patients. Test-retest reliability was excellent for all parameters (intraclass correlation (ICC) > 0.81) except for gait velocity (ICC > 0.55). The sensor-based system was able to accurately capture spatio-temporal gait parameters as compared to the reference camera-based system for normal and impaired gait. The system's high retest reliability renders the use in recurrent clinical measurements and in long-term applications feasible.

Stride segmentation during free walk movements using multi-dimensional subsequence dynamic time warping on inertial sensor data.

Changes in gait patterns provide important information about individuals' health. To perform sensor based gait analysis, it is crucial to develop methodologies to automatically segment single strides from continuous movement sequences. In this study we developed an algorithm based on time-invariant template matching to isolate strides from inertial sensor signals. Shoe-mounted gyroscopes and accelerometers were used to record gait data from 40 elderly controls, 15 patients with Parkinson's disease and 15 geriatric patients. Each stride was manually labeled from a straight 40 m walk test and from a video monitored free walk sequence. A multi-dimensional subsequence Dynamic Time Warping (msDTW) approach was used to search for patterns matching a pre-defined stride template constructed from 25 elderly controls. F-measure of 98% (recall 98%, precision 98%) for 40 m walk tests and of 97% (recall 97%, precision 97%) for free walk tests were obtained for the three groups. Compared to conventional peak detection methods up to 15% F-measure improvement was shown. The msDTW proved to be robust for segmenting strides from both standardized gait tests and free walks. This approach may serve as a platform for individualized stride segmentation during activities of daily living.

Neuromuscular adaptations after osseointegration of a bone-anchored prosthesis in a unilateral transfemoral amputee - a case study.

PURPOSE: Many individuals with a lower limb amputation experience problems with the fitting of the socket of their prosthesis, leading to dissatisfaction or device rejection. Osseointegration (OI)- the implantation of a shaft directly interfacing with the remaining bone- is an alternative for these patients. In this observational study, we investigated how bone anchoring influences neuromuscular parameters during balance control in a patient with a unilateral transfemoral amputation. MATERIAL AND METHODS: Center of pressure (CoP) and electromyography (EMG) signals from muscles controlling the hip and the ankle of the intact leg were recorded during quiet standing six months before and one and a half years after this patient underwent an OI surgery. Results were compared to a control group of nine able-bodied individuals. RESULTS: Muscle co-activation and EMG intensity decreased after bone anchoring, approaching the levels of able-bodied individuals. Muscle co-activation controlling the ankle decreased in the high-frequency range, and the EMG intensity spectrum decreased in the lower-frequency range for all muscles when vision was allowed. With eyes closed, the ankle extensor muscle showed an increased EMG intensity in the high-frequency range post-surgery. CoP length increased in the mediolateral direction of the amputated leg. CONCLUSIONS: These findings point to shifts in the patient's neuromuscular profile towards the one of able-bodied individuals.

A cross-sectional study of nutritional status in healthy, young, physically-active German omnivores, vegetarians and vegans reveals adequate vitamin B12 status in supplemented vegans.

BACKGROUND/OBJECTIVE: Plant-based diets reduce the risk of cardiovascular disease but also increase the risk of certain micronutrient deficiencies, particularly, of vitamin B12 (B12). The extent to which the unsupervised use of oral nutrient supplements is sufficient to prevent these deficiencies is not well established. We analyzed nutrient intake, laboratory biomarkers, supplementation behavior, and B12 status adequacy amongst young, healthy, physically active omnivores, lacto-ovo-vegetarians and vegans from Germany. METHODS: We recruited 115 participants (n = 40 omnivores; n = 37 lacto-ovo-vegetarians, and n = 38 vegans) with comparable age, sex, marital status, physical activity and educational levels through online advertisements and local newspapers in Freiburg, Germany. RESULTS: Energy intake and macronutrient distribution were comparable across diets. Major differences included intake of fiber, cholesterol, and several vitamins. Vegans had the lowest intake of B12 from foods (0.43 (0.58) µg/d), compared to omnivores (2.14 (2.29) µg/d) and lacto-ovo-vegetarians (0.98 (1.34) µg/day). Multivariate analysis of 36 blood biomarkers revealed that three major classes of biomarkers contributed the most to the clustering of individuals by dietary group, namely, biomarkers of B12 status (B12, holoTC, Hcy), iron (iron, ferritin, transferrin) and lipid metabolism (vitamin A, HDL, LDL, total cholesterol, TAG). This suggests that nutrients that modify the metabolic pathways represented by these biomarkers have the most penetrating effect on health status across diets. Analysis of B12 status (including 4cB12) revealed adequacy in omnivores and vegans, and a poorer B12 status amongst lacto-ovo-vegetarians. Fewer lacto-ovo-vegetarians used B12 supplements compared to vegans (51% versus 90%). CONCLUSIONS: Even amongst homogeneously healthy Germans, each diet manifested with measurable differences in dietary intakes and biomarkers of health. Plant-based diets, in particular the vegan diet, exhibited the most favorable patterns of lipid metabolism and glycemic control, but the lowest food intake of B12. Supplementation of healthy vegans with B12 (median 250 µg B12/day, over 2 years) secured an adequate B12 status that was comparable to that of healthy omnivores.Clinical Trial Registry: German Clinical Trial register number: DRKS00027425.

Plant-based diets, in particular the vegan diet, exhibited the most favorable patterns of lipid metabolism and glycemic control, but the lowest food intake of B12.Analysis of B12 status (including 4cB12) revealed adequacy in omnivores and vegans, and a poorer B12 status amongst lacto-ovo-vegetarians.Supplementation with B12 (median 250 µg B12/day, over 1 year) in healthy physically-active vegans secured an adequate B12 status that was comparable to that of healthy omnivores.

Evaluation of a neural network-based control strategy for a cost-effective externally-powered prosthesis.

This paper presents a control strategy that compensates for the nonlinearity in the inexpensive sensors and hardware of a cost effective prosthetic hand. The control strategy uses neural network-based force control and sensory feedback to detect disturbance induced by slippage. The neural network approach is chosen over other nonlinear models because it is easy to implement and it offered the additional advantage of having its parameters easily adjusted over the life span of the device. The proposed strategy was evaluated on a functional multi-digit underactuated prosthetic hand. The initial and incremental forces exerted from each finger were adjusted to balance the amount of disturbance and the deformation of the objects. Experiments were conducted to test the performance of the protocol in situations encountered in activities of daily living. The displacement of each object under three grasping configurations was measured as a performance criterion while the object's mass was changed. The results showed that with the adjusted parameters for each grasping configuration, the control strategy was able to detect the dynamic changes in mass of the object and was also able to successfully adjust the grasping force before the object drops from the hand.

Influence of Augmented Visual Feedback on Balance Control in Unilateral Transfemoral Amputees.

Patients with a lower limb amputation rely more on visual feedback to maintain balance than able-bodied individuals. Altering this sensory modality in amputees thus results in a disrupted postural control. However, little is known about how lower limb amputees cope with augmented visual information during balance tasks. In this study, we investigated how unilateral transfemoral amputees incorporate visual feedback of their center of pressure (CoP) position during quiet standing. Ten transfemoral amputees and ten age-matched able-bodied participants were provided with real-time visual feedback of the position of their CoP while standing on a pressure platform. Their task was to keep their CoP within a small circle in the center of a computer screen placed at eye level, which could be achieved by minimizing their postural sway. The visual feedback was then delayed by 250 and 500 ms and was combined with a two- and five-fold amplification of the CoP displacements. Trials with eyes open without augmented visual feedback as well as with eyes closed were further performed. The overall performance was measured by computing the sway area. We further quantified the dynamics of the CoP adjustments using the entropic half-life (EnHL) to study possible physiological mechanisms behind postural control. Amputees showed an increased sway area compared to the control group. The EnHL values of the amputated leg were significantly higher than those of the intact leg and the dominant and non-dominant leg of controls. This indicates lower dynamics in the CoP adjustments of the amputated leg, which was compensated by increasing the dynamics of the CoP adjustments of the intact leg. Receiving real-time visual feedback of the CoP position did not significantly reduce the sway area neither in amputees nor in controls when comparing with the eyes open condition without visual feedback of the CoP position. Further, with increasing delay and amplification, both groups were able to compensate for small visual perturbations, yet their dynamics were significantly lower when additional information was not received in a physiologically relevant time frame. These findings may be used for future design of neurorehabilitation programs to restore sensory feedback in lower limb amputees.

Neural Implants Without Electronics: A Proof-of-Concept Study on a Human Skin Model.

Objective: Chronic neural implants require energy and signal supply. The objective of this work was to evaluate a multichannel transcutaneous coupling approach in an ex vivo split-concept study, which minimizes the invasiveness of such an implant by externalizing the processing electronics. Methods: Herein, the experimental work focused on the transcutaneous energy and signal transmission. The performance was discussed with widely evaluated concepts of neural interfaces in the literature. Results: The performance of the transcutaneous coupling approach increased with higher channel count and higher electrode pitches. Electrical crosstalk among channels was present, but acceptable for the stimulation of peripheral nerves. Conclusions: Transcutaneous coupling with extracorporeal transmitting arrays and subcutaneous counterparts provide a promising alternative to the inductive concept particularly when a fully integration of the system in a prosthetic shaft is intended. The relocation of the electronics can potentially prevent pressure sores, improve accessibility for maintenance and increase lifetime of the implant.

Fabrication and validation of reference structures for the localization of subdural standard- and micro-electrodes in MRI.

OBJECTIVE: Report simple reference structure fabrication and validate the precise localization of subdural micro- and standard electrodes in magnetic resonance imaging (MRI) in phantom experiments. APPROACH: Electrode contacts with diameters of 0.3 mm and 4 mm are localized in 1.5 T MRI using reference structures made of silicone and iron oxide nanoparticle doping. The precision of the localization procedure was assessed for several standard MRI sequences and implant orientations in phantom experiments and compared to common clinical localization procedures. MAIN RESULTS: A localization precision of 0.41 ± 0.20 mm could be achieved for both electrode diameters compared to 1.46 ± 0.69 mm that was achieved for 4 mm standard electrode contacts localized using a common clinical standard method. The new reference structures are intrinsically bio-compatible, and they can be detected with currently available feature detection software so that a clinical implementation of this technology should be feasible. SIGNIFICANCE: Neuropathologies are increasingly diagnosed and treated with subdural electrodes, where the exact localization of the electrode contacts with respect to the patient's cortical anatomy is a prerequisite for the procedure. Post-implantation electrode localization using MRI may be advantageous compared to the common alternative of CT-MRI image co-registration, as it avoids systematic localization errors associated with the co-registration itself, as well as brain shift and implant movement. Additionally, MRI provides superior soft tissue contrast for the identification of brain lesions without exposing the patient to ionizing radiation. Recent studies show that smaller electrodes and high-density electrode grids are ideal for clinical and research purposes, but the localization of these devices in MRI has not been demonstrated.

Electrical connectors for neural implants: design, state of the art and future challenges of an underestimated component.

Technological advances in electrically active implantable devices have increased the complexity of hardware design. In particular, the increasing number of stimulation and recording channels requires innovative approaches for connectors that interface electrodes with the implant circuitry. OBJECTIVE: This work aims to provide a common theoretical ground for implantable connector development with a focus on neural applications. APPROACH: Aspects and experiences from several disciplines are compiled from an engineering perspective to discuss the state of the art of connector solutions. Whenever available, we also present general design guidelines. MAIN RESULTS: Degradation mechanisms, material stability and design rules in terms of biocompatibility and biostability are introduced. Considering contact physics, we address the design and characterization of the contact zone and review contaminants, wear and contact degradation. For high-channel counts and body-like environments, insulation can be even more crucial than the electrical connection itself. Therefore, we also introduce the requirements for electrical insulation to prevent signal loss and distortion and discuss its impact on the practical implementation. SIGNIFICANCE: A final review is dedicated to the state of the art connector concepts, their mechanical setup, electrical performance and the interface to other implant components. We conclude with an outlook for possible approaches for the future generations of implants.

Perturbation Treadmill Training Improves Clinical Characteristics of Gait and Balance in Parkinson's Disease.

BACKGROUND: Impaired gait and postural stability are cardinal motor symptoms in Parkinson's disease (PD). Treadmill training improves gait characteristics in PD. OBJECTIVE: This study investigates if postural perturbations during treadmill training improve motor performance and particularly gait and postural stability in PD. METHODS: This work presents secondary outcome measures of a pilot randomized controlled trial. PD patients (n = 43) recruited at the University Hospital Erlangen were randomly allocated to the experimental (perturbation treadmill training, PTT, n = 21) or control group (conventional treadmill training, CTT, n = 22). Outcome measures were collected at baseline, after 8 weeks of intervention, and 3 months follow-up. Motor impairment was assessed by the Unified Parkinson Disease Rating Scale part-III (UPDRS-III), Postural Instability and Gait Difficulty score (PIGD), and subitems 'Gait' and 'Postural stability' by an observer blinded to the randomization. Intervention effects were additionally compared to progression rates of a matched PD cohort (n = 20) receiving best medical treatment (BMT). RESULTS: Treadmill training significantly improved UPDRS-III motor symptoms in both groups with larger effect sizes for PTT (-38%) compared to CTT (-20%). In the PTT group solely, PIGD -34%, and items 'Gait' -50%, and 'Postural stability' -40% improved significantly in comparison to CTT (PIGD -24%, 'Gait' -22%, 'Postural stability' -33%). Positive effects persisted in PTT after 3 months and appeared to be beneficial compared to BMT. CONCLUSIONS: Eight weeks of PTT showed superior improvements of motor symptoms, particularly gait and postural stability. Sustainable effects indicate that PTT may be an additive therapy option for gait and balance deficits in PD.

Exploring gait adaptations to perturbed and conventional treadmill training in Parkinson's disease: Time-course, sustainability, and transfer.

BACKGROUND: Gait impairment is a major motor symptom in Parkinson's disease (PD), and treadmill training is an effective non-pharmacological treatment option. RESEARCH QUESTION: In this study, the time course, sustainability and transferability of gait adaptations to treadmill training with and without additional postural perturbations were investigated. METHODS: 38 PD patients (Hoehn & Yahr 1-3.5) were randomly allocated to eight weeks of treadmill training, performed twice-weekly for 40 min either with (perturbation treadmill training [PTT], n = 18) or without (conventional treadmill training [CTT], n = 20) additional perturbations to the treadmill surface. Spatiotemporal gait parameters were assessed during treadmill walking on a weekly basis (T0-T8), and after three months follow-up (T9). Additional overground gait analyses were performed at T0 and T8 to investigate transfer effects. RESULTS: Treadmill gait variability reduced linearly over the course of 8 weeks in both groups (p < .001; Cohen's d (range): -0.53 to -0.84). Only the PTT group significantly improved in other gait parameters (stride length/time, stance-/swing time), with stride time showing a significant between-group interaction effect (Cohen's d = 0.33; p = .05). Additional between-group interactions indicated more sustained improvements in stance (Cohen's d = 0.85; p = .02) and swing time variability in the PTT group (Cohen's d = 0.82; p = .03) at T9. Overground gait improvements at T8 existed only in stance (d = -0.73; p = .04) and swing time (d = 0.73; p = .04). DISCUSSION: Treadmill stride-to-stride variability reduced substantially and linearly, but transfer to overground walking was limited. Adding postural perturbations tended to increase efficacy and sustainability of several gait parameters. However, since between-group effects were small, more work is necessary to support these findings.

Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system.

The somatosensory system contributes substantially to the integration of multiple sensor modalities into perception. Tactile sensations, proprioception and even temperature perception are integrated to perceive embodiment of our limbs. Damage of somatosensory networks can severely affect the execution of daily life activities. Peripheral injuries are optimally corrected via direct interfacing of the peripheral nerves. Recent advances in implantable devices, stimulation paradigms, and biomimetic sensors enabled the restoration of natural sensations after amputation of the limb. The refinement of stimulation patterns to deliver natural feedback that can be interpreted intuitively such to prescind from long-learning sessions is crucial to function restoration. For this review, we collected state-of-the-art knowledge on the evolution of stimulation paradigms from single fiber stimulation to the eliciting of multisensory sensations. Data from the literature are structured into six sections: (a) physiology of the somatosensory system; (b) stimulation of single fibers; (c) restoral of multisensory percepts; (d) closure of the control loop in hand prostheses; (e) sensory restoration and the sense of embodiment, and (f) methodologies to assess stimulation outcomes. Full functional recovery demands further research on multisensory integration and brain plasticity, which will bring new paradigms for intuitive sensory feedback in the next generation of limb prostheses.

Mobile Stride Length Estimation With Deep Convolutional Neural Networks.

OBJECTIVE: Accurate estimation of spatial gait characteristics is critical to assess motor impairments resulting from neurological or musculoskeletal disease. Currently, however, methodological constraints limit clinical applicability of state-of-the-art double integration approaches to gait patterns with a clear zero-velocity phase. METHODS: We describe a novel approach to stride length estimation that uses deep convolutional neural networks to map stride-specific inertial sensor data to the resulting stride length. The model is trained on a publicly available and clinically relevant benchmark dataset consisting of 1220 strides from 101 geriatric patients. Evaluation is done in a tenfold cross validation and for three different stride definitions. RESULTS: Even though best results are achieved with strides defined from midstance to midstance with average accuracy and precision of , performance does not strongly depend on stride definition. The achieved precision outperforms state-of-the-art methods evaluated on the same benchmark dataset by . CONCLUSION: Due to the independence of stride definition, the proposed method is not subject to the methodological constrains that limit applicability of state-of-the-art double integration methods. Furthermore, it was possible to improve precision on the benchmark dataset. SIGNIFICANCE: With more precise mobile stride length estimation, new insights to the progression of neurological disease or early indications might be gained. Due to the independence of stride definition, previously uncharted diseases in terms of mobile gait analysis can now be investigated by retraining and applying the proposed method.

Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty.

BACKGROUND: Despite the general success of total knee arthroplasty (TKA) regarding patient-reported outcome measures, studies investigating gait function have shown diverse functional outcomes. Mobile sensor-based systems have recently been employed for accurate clinical gait assessments, as they allow a better integration of gait analysis into clinical routines as compared to laboratory based systems. RESEARCH QUESTION: In this study, we sought to examine whether an accurate assessment of gait function of knee osteoarthritis patients with respect to surgery outcome evaluation after TKA using a mobile sensor-based gait analysis system is possible. METHODS: A foot-worn sensor-based system was used to assess spatio-temporal gait parameters of 24 knee osteoarthritis patients one day before and one year after TKA, and in comparison to matched control participants. Patients were clustered into positive and negative responder groups using a heuristic approach regarding improvements in gait function. Machine learning was used to predict surgery outcome based on pre-operative gait parameters. RESULTS: Gait function differed significantly between controls and patients. Patient-reported outcome measures improved significantly after surgery, but no significant global gait parameter difference was observed between pre- and post-operative status. However, the responder groups could be correctly predicted with an accuracy of up to 89% using pre-operative gait parameters. Patients exhibiting high pre-operative gait function were more likely to experience a functional decrease after surgery. Important gait parameters for the discrimination were stride time and stride length. SIGNIFICANCE: The early identification of post-surgical functional outcomes of patients is of great importance to better inform patients pre-operatively regarding surgery success and to improve post-surgical management.

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards.

BACKGROUND: Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records, and is therefore difficult for caregivers to combine and analyze. One possible solution to overcome these limitations is the interconnection of medical devices via the Internet using a distributed platform, namely the Internet of Things. This approach allows data from different sources to be combined in order to better diagnose patient health status and identify possible anticipatory actions. METHODS: This work introduces the concept of the Internet of Health Things (IoHT), focusing on surveying the different approaches that could be applied to gather and combine data on vital signs in hospitals. Common heuristic approaches are considered, such as weighted early warning scoring systems, and the possibility of employing intelligent algorithms is analyzed. RESULTS: As a result, this article proposes possible directions for combining patient data in hospital wards to improve efficiency, allow the optimization of resources, and minimize patient health deterioration. CONCLUSION: It is concluded that a patient-centered approach is critical, and that the IoHT paradigm will continue to provide more optimal solutions for patient management in hospital wards.

Dynamic footprint based locomotion sway assessment in α-synucleinopathic mice using Fast Fourier Transform and Low Pass Filter.

BACKGROUND: Sway is a crucial gait characteristic tightly correlated with the risk of falling in patients with Parkinsons disease (PD). So far, the swaying pattern during locomotion has not been investigated in rodent models using the analysis of dynamic footprint recording obtained from the CatWalk gait recording and analysis system. NEW METHODS: We present three methods for describing locomotion sway and apply them to footprint recordings taken from C57BL6/N wild-type mice and two different α-synuclein transgenic PD-relevant mouse models (α-synm-ko, α-synm-koxα-synh-tg). Individual locomotion data were subjected to three different signal processing analytical approaches: the first two methods are based on Fast Fourier Transform (FFT), while the third method uses Low Pass Filters (LPF). These methods use the information associated with the locomotion sway and generate sway-related parameters. RESULTS: The three proposed methods were successfully applied to the footprint recordings taken from all paws as well as from front/hind-paws separately. Nine resulting sway-related parameters were generated and successfully applied to differentiate between the mouse models under study. Namely, α-synucleinopathic mice revealed higher sway and sway itself was significantly higher in the α-synm-koxα-synh-tg mice compared to their wild-type littermates in eight of the nine sway-related parameters. COMPARISON WITH EXISTING METHOD: Previous locomotion sway index computation is based on the estimated center of mass position of mice. CONCLUSIONS: The methods presented in this study provide a sway-related gait characterization. Their application is straightforward and may lead to the identification of gait pattern derived biomarkers in rodent models of PD.

Dynamic footprints of α-synucleinopathic mice recorded by CatWalk gait analysis.

Characterizing gait is important in the study of movement disorders, also in clinical mouse models. Gait data are therefore necessary for the development of gait analysis methods and the study of diseases. This article presents gait data of two α-synucleinopathic transgenic mouse models and their non-transgenic littermate, backcrossed into the C57BL/6N genetic background. The animal gait was recorded using CatWalk system, which provides the information for each run about the paw positions, paw print sizes, and paw intensities as a function of time or video frame. A total of 90 run data files are provided in this article.

Perturbation During Treadmill Training Improves Dynamic Balance and Gait in Parkinson's Disease: A Single-Blind Randomized Controlled Pilot Trial.

BACKGROUND: Gait and balance dysfunction are major symptoms in Parkinson's disease (PD). Treadmill training improves gait characteristics in this population but does not reflect the dynamic nature of controlling balance during ambulation in everyday life contexts. OBJECTIVE: To evaluate whether postural perturbations during treadmill walking lead to superior effects on gait and balance performance compared with standard treadmill training. METHODS: In this single-blind randomized controlled trial, 43 PD patients (Hoehn & Yahr stage 1-3.5) were assigned to either an 8-week perturbed treadmill intervention (n = 21) or a control group (n = 22) training on the identical treadmill without perturbations. Patients were assessed at baseline, postintervention, and at 3 months' follow-up. Primary endpoints were overground gait speed and balance (Mini-BESTest). Secondary outcomes included fast gait speed, walking capacity (2-Minute Walk Test), dynamic balance (Timed Up-and-Go), static balance (postural sway), and balance confidence (Activities-Specific Balance Confidence [ABC] scale). RESULTS: There were no significant between-group differences in change over time for the primary outcomes. At postintervention, both groups demonstrated similar improvements in overground gait speed ( P = .009), and no changes in the Mini-BESTest ( P = .641). A significant group-by-time interaction ( P = .048) existed for the Timed Up-and-Go, with improved performance only in the perturbation group. In addition, the perturbation but not the control group significantly increased walking capacity ( P = .038). Intervention effects were not sustained at follow-up. CONCLUSIONS: Our primary findings suggest no superior effect of perturbation training on gait and balance in PD patients. However, some favorable trends existed for secondary gait and dynamic balance parameters, which should be investigated in future trials.

Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks.

Measurement of stride-related, biomechanical parameters is the common rationale for objective gait impairment scoring. State-of-the-art double-integration approaches to extract these parameters from inertial sensor data are, however, limited in their clinical applicability due to the underlying assumptions. To overcome this, we present a method to translate the abstract information provided by wearable sensors to context-related expert features based on deep convolutional neural networks. Regarding mobile gait analysis, this enables integration-free and data-driven extraction of a set of eight spatio-temporal stride parameters. To this end, two modeling approaches are compared: a combined network estimating all parameters of interest and an ensemble approach that spawns less complex networks for each parameter individually. The ensemble approach is outperforming the combined modeling in the current application. On a clinically relevant and publicly available benchmark dataset, we estimate stride length, width and medio-lateral change in foot angle up to -0.15 ± 6.09 cm, -0.09 ± 4.22 cm and 0.13 ± 3.78° respectively. Stride, swing and stance time as well as heel and toe contact times are estimated up to ±0.07, ±0.05, ±0.07, ±0.07 and ±0.12 s respectively. This is comparable to and in parts outperforming or defining state of the art. Our results further indicate that the proposed change in the methodology could substitute assumption-driven double-integration methods and enable mobile assessment of spatio-temporal stride parameters in clinically critical situations as, e.g., in the case of spastic gait impairments.