Navrag Singh

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Singh

First Name

Navrag

ORCID

0000-0001-8074-041X

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Publications 1 - 10 of 47

Achieving ecological validity in mobility assessment: Validating a wearable sensor technology for comprehensive gait assessment
Mohammadi, Mostafa; Singh, Navrag; Hitz, Marco; et al. (2017)
2017 IEEE 3rd International Forum on Research and Technologies for Society and Industry (RTSI)
The role of electrode placement in subthalamic nucleus deep brain stimulation for improving gait in Parkinson’s Disease
Mei, Zhongke; Hofer, Anna-Sophie; Baumann, Christian; et al. (2026)
Clinical Neurophysiology
Objective To investigate the relationship between the spatial location of active electrode contacts in subthalamic nucleus deep brain stimulation (STN-DBS) and changes in gait performance in patients with Parkinson’s disease (PwPD). Methods This observational study included 49 PwPD who underwent bilateral STN-DBS. Spatiotemporal gait parameters were assessed before surgery and six months post-implantation using motion capture. Both mean values and variability of gait parameters were analyzed. Active contact locations were normalized using a voxel-based approach and statistically associated with gait outcomes. Results STN-DBS led to significant reductions in stride time, stance time, swing time, and step time, alongside increased step width and temporal gait variability. Gait improvements were associated with specific stimulation sites: the postero-superior STN region was most effective for enhancing mean spatial parameters (e.g., stride length, walking speed), while the antero-superior region was optimal for reducing temporal variability. Patients stimulated in these regions showed significantly better gait outcomes than those stimulated elsewhere. Conclusions Gait improvements were differentially associated with the spatial location of stimulation electrode within the STN, suggesting region-specific modulation of mean spatial and temporal variability gait parameters. Significance These findings support precision targeting of stimulation sites to optimize patient-specific gait outcomes, advancing personalized DBS therapy in Parkinson’s disease.
Extreme Levels of Noise Constitute a Key Neuromuscular Deficit in the Elderly
Singh, Navrag; König, Niklas; Arampatzis, Adamantios; et al. (2012)
PLoS ONE
Fluctuations during isometric force production tasks occur due to the inability of musculature to generate purely constant submaximal forces and are considered to be an estimation of neuromuscular noise. The human sensori-motor system regulates complex interactions between multiple afferent and efferent systems, which results in variability during functional task performance. Since muscles are the only active component of the motor system, it therefore seems reasonable that neuromuscular noise plays a key role in governing variability during both standing and walking. Seventy elderly women (including 34 fallers) performed multiple repetitions of isometric force production, quiet standing and walking tasks. No relationship between neuromuscular noise and functional task performance was observed in either the faller or the non-faller cohorts. When classified into groups with either nominal (group NOM, 25th –75th percentile) or extreme (either too high or too low, group EXT) levels of neuromuscular noise, group NOM demonstrated a clear association (r2>0.23, p<0.05) between neuromuscular noise and variability during task performance. On the other hand, group EXT demonstrated no such relationship, but also tended to walk slower, and had lower stride lengths, as well as lower isometric strength. These results suggest that neuromuscular noise is related to the quality of both static and dynamic functional task performance, but also that extreme levels of neuromuscular noise constitute a key neuromuscular deficit in the elderly.
Complexities and challenges of translating intervention success to real world gait in people with Parkinson's disease
Lang, Charlotte; van Dieen, Jaap H.; Brodie, Matthew A.; et al. (2024)
Frontiers in Neurology
Background Unstable gait leading to falls negatively impacts the quality of life in many people with Parkinson's disease (PD). Systematic review evidence provides moderate to strong evidence of efficacy for a wide range of physiotherapy-based interventions to reduce gait impairment. However, outcomes have often focused on gait assessments conducted in controlled laboratory or clinical environments.Objective This perspective investigates the complexities and challenges of conducting real-world gait assessments in people with PD and the factors that may influence the translation from improved lab-assessed gait to improved real-world gait.Methods Through a thorough review of current literature, we present an in-depth analysis of current methodological approaches to real-world gait assessments and the challenges that may influence the translation of an intervention's success from lab-based outcomes to improved walking during daily life.Results We identified six key factors that may influence the translation of intervention success into real-world environments at different stages of the process. These factors comprise the gait intervention, parameters analyzed, sensor setup, assessment protocols, characteristics of walking bouts, and medication status. We provide recommendations for each factor based on our synthesis of current literature.Conclusion This perspective emphasizes the importance of measuring intervention success outside of the laboratory environment using real-world gait assessments. Our findings support the need for future studies to bridge the gap between proven efficacy for gait as assessed in controlled laboratory environments and real-world impact for people with PD.
The effects of weight-bearing manipulations on gait and its underlying neural control mechanisms in toe walking children
Gwerder, Michelle; Visscher, Rosa M.S.; Spescha, Anusha; et al. (2025)
Frontiers in Human Neuroscience
In toe walking children, impaired maturation of neuromotor control often leads to persistent use of immature motor programs. Understanding the underlying etiology of toe walking in children with cerebral palsy (CP) and idiopathic toe walking (ITW) is crucial for advancing rehabilitation strategies. This study examined gait adaptations and H-reflex responses to varied weight-bearing conditions to determine whether children with ITW and CP exhibit distinct neuromotor control strategies compared to typically developing (TD) peers. Eight children with CP (mean age 12.9 ± 2.1 years), eight with ITW (8.6 ± 1.9 years), and 19 TD children (10.0 ± 2.6 years) walked on a treadmill under three conditions: normal bodyweight, 30% bodyweight unloading, and 30% additional bodyweight. Linear mixed-effects models assessed spatiotemporal gait parameters, margin of stability, gait variability, and H-reflex responses. Bodyweight unloading increased single-limb support time, while reducing double-limb support time and antero-posterior margin of stability across groups (p=0.01). ITW children exhibited increased gait variability (p=0.01) under bodyweight unloading, while CP children showed no change. H-reflex amplitudes decreased under bodyweight unloading in TD children, while CP children exhibited hyperreflexia (p=0.05). Discussion: The findings of this exploratory study suggest that toe walking is associated with distinct adaptive strategies in ITW and CP children to compensate for environmental challenges. In ITW, increased variability under bodyweight unloading may reflect exploratory motor control, whereas CP children relied on stiffening strategies, marked by reduced variability and hyperreflexia, indicating limited adaptability and less efficient gait patterns. These results imply that similar biomechanical constraints evoke divergent neuromotor adaptations in ITW and CP children.
Effects of single-session perturbation-based balance training with progressive intensities on resilience and dynamic gait stability in healthy older adults
Zhu, Ringo Tang-Long; Schulte, Friederike A.; Singh, Navrag; et al. (2025)
Frontiers in Bioengineering and Biotechnology
Introduction: Single-session perturbation-based balance training (PBT) has demonstrated improvements in dynamic stability during the initial step following perturbation in older adults. However, its broader effects on comprehensive balance recovery remain inconclusive. This pilot laboratory-based randomized controlled study investigated the impact of personalized single-session PBT on reactive balance control during walking, employing advanced stability analysis techniques. Methods: Ten participants in the training group (67.1 ± 2.8 years; 5 males & 5 females) underwent a single session consisting of 32 unpredictable treadmill-induced slips and trips of progressively increasing intensity, while ten participants in the control group (72.8 ± 5.2 years; 5 males & 5 females) engaged in unperturbed treadmill walking. Key outcome measures included margin of stability (MoS) parameters: minimum MoS and the number of recovery steps, and resilience parameters: peak instability and recovery time, assessed at baseline, immediately post-intervention, and 3 months post-intervention following an unexpected treadmill slip. Results: In the training group, participants exhibited significant increases in minimum MoS values immediately post-intervention (−33 ± 84 mm; p < 0.001) and 3 months post-intervention (−71 ± 70 mm; p < 0.01) as compared to pre-intervention (−140 ± 87 mm); they also showed a significant reduction in peak instability immediately post-intervention (34 ± 14 mm; p = 0.019) as compared to pre-intervention (57 ± 25 mm). These changes were not observed in the control group. However, neither group demonstrated significant alterations in the number of recovery steps or recovery time across the different assessment periods. Discussion and conclusion: In conclusion, single-session PBT enhanced reactive balance control by improving the magnitude of post-perturbation responses, but it did not significantly influence the speed of recovery to baseline conditions.
The Influence of Backpack Weight and Hip Belt Tension on Movement and Loading in the Pelvis and Lower Limbs during Walking
Oberhofer, Katja; Wettenschwiler, Patrick D.; Singh, Navrag; et al. (2018)
Applied Bionics and Biomechanics
Identifying treatment non-responders based on pre-treatment gait characteristics - A machine learning approach
Visscher, Rosa M.S.; Murer, Julia; Fahimi, Fatemeh; et al. (2023)
Heliyon
Background: Paediatric movement disorders such as cerebral palsy often negatively impact walking behaviour. Although clinical gait analysis is usually performed to guide therapy decisions, not all respond positively to their assigned treatment. Identifying these individuals based on their pre-treatment characteristics could guide clinicians towards more appropriate and personalized interventions. Using routinely collected pre-treatment gait and anthropometric features, we aimed to assess whether standard machine learning approaches can be effective in identifying patients at risk of negative treatment outcomes. Methods: Observational data of 119 patients with movement disorders were retrospectively extracted from a local clinical database, comprising sagittal joint angles and spatiotemporal parameters, derived from motion capture data pre- and post-treatment (physiotherapy, orthosis, botulin toxin injections, or surgery). Participants were labelled based on their change in gait profile score (GPS, non-responders with a decline in GPS of <1.6° vs. responders). Their pre-treatment features (sagittal joint angles, spatiotemporal parameters, anthropometrics) were used to train a support vector machine classifier with 5-fold cross-validation and Bayesian optimization within a MATLAB-based Classification Learner App. Results: An average accuracy of 88.2 ± 0.5 % was achieved for identifying participants whose gait will not respond to treatment, with 64 % true negative rate and an area under the curve of 88 %. Conclusion: Overall, a classical machine learning model was able to identify patients at risk of not responding to treatment, based on gait features and anthropometrics collected prior to treatment. The output of such a model could function as a warning signal, notifying clinicians that a certain individual might not respond well to the standard of care and that a more personalized intervention might be needed.
A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy—Which markers work best for which gait patterns?
Kim, Yong K.; Visscher, Rosa; Viehweger, Elke; et al. (2022)
PLoS ONE
Neuromotor pathologies often cause motor deficits and deviations from typical locomotion, reducing the quality of life. Clinical gait analysis is used to effectively classify these motor deficits to gain deeper insights into resulting walking behaviours. To allow the ensemble averaging of spatio-temporal metrics across individuals during walking, gait events, such as initial contact (IC) or toe-off (TO), are extracted through either manual annotation based on video data, or through force thresholds using force plates. This study developed a deep-learning long short-term memory (LSTM) approach to detect IC and TO automatically based on foot-marker kinematics of 363 cerebral palsy subjects (age: 11.8 ± 3.2). These foot-marker kinematics, including 3D positions and velocities of the markers located on the hallux (HLX), calcaneus (HEE), distal second metatarsal (TOE), and proximal fifth metatarsal (PMT5), were extracted retrospectively from standard barefoot gait analysis sessions. Different input combinations of these four foot-markers were evaluated across three gait subgroups (IC with the heel, midfoot, or forefoot). For the overall group, our approach detected 89.7% of ICs within 16ms of the true event with a 18.5% false alarm rate. For TOs, only 71.6% of events were detected with a 33.8% false alarm rate. While the TOE|HEE marker combination performed well across all subgroups for IC detection, optimal performance for TO detection required different input markers per subgroup with performance differences of 5-10%. Thus, deep-learning LSTM based detection of IC events using the TOE|HEE markers offers an automated alternative to avoid operator-dependent and laborious manual annotation, as well as the limited step coverage and inability to measure assisted walking for force plate-based detection of IC events.
Key performance indicators and leg positioning for the kick-start in competitive swimmers
Burkhardt, David; Born, Dennis-Peter; Singh, Navrag; et al. (2023)
Sports Biomechanics
The aim of the study was to (1) assess the test–retest reliability of a novel performance analysis system for swimming (KiSwim) including an instrumented starting block and optical motion capture system, (2) identify key performance indicators (KPI) for the kick-start, (3) determine the most beneficial position of the strong leg and (4) investigate the effect of acute reversal of leg positioning. During three sessions, kick-starts of 15 competitive swimmers were investigated. Eighteen kinematic and kinetic parameters showed high reliability (ICC>0.75) from which principal component analysis identified seven KPI (i.e., time to 15 m, time on-block, depth at 7.5 m, horizontal take-off velocity, horizontal impulse back plate, horizontal peak force back plate and vertical peak force front plate). For the preferred start position, the back plate showed a higher horizontal peak force (0.71 vs. 0.96 x body mass; p < 0.001) and impulse (0.191 vs. 0.28Ns/BW; p < 0.001) compared to front plate. Acute reversal of the leg position reduced performance (i.e., increased time to 15 m and reduced horizontal take-off velocity). However, plate-specific kinetic analysis revealed a larger horizontal peak force (p < 0.001) and impulse (p < 0.001) for the back compared to the front plate in any start position investigated. Therefore, swimmers are encouraged to position the strong leg in the back. (© 2020 Swiss Federal Institute of Sport).

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