Biology subjects

Melzer, I.

Publications and source records attributed to Melzer, I..

4 recordsLinked to original sources

bioRxiv2023

Comparative Analysis of Cameras and Software Tools for Skeleton Tracking

BackgroundSkeleton tracking is a valuable tool for monitoring user performance and has been performed with different sensors and software tools. It enables to quantify 3D motion accurately. We present a comparative analysis of cameras and software tools utilized in skeleton tracking. We describe an experimental design and analysis methods with four steps. Specifically, we conducted an analysis comparing two ZED-2i cameras with a RealSense camera using commercial skeleton tracking algorithms. MethodsThe comparative analysis methodology describes the experimental design and analysis methods for comparing kinematic data from both upper and lower extremities. An experiment to evaluate the performance of three different cameras (RealSense, ZED2mm, and ZED4mm) and three skeleton tracking algorithms (PyZED, Nuitrack, and MediaPipe) was performed with 16 participants. The participants were required to walk along a 6-meter-long path while moving their hands up and down horizontally. Ground truth was measured by a Vicon 3D motion analysis system. Two groups of features corresponding to the upper and lower extremities were derived from the raw data and compared using two methods. In the first method, the RMSE values were compared to the data from the Vicon system. The RMSE results were also combined using two grading techniques with different feature importance weights to determine the camera with the lowest RMSE. In the second method, a linear mix model with a Wald statistical test was applied. ResultsThe ZED-2i cameras outperformed the RealSense camera across upper- and lower-extremity features and different weights. The ZED2mm camera showed better average median grading, lower standard deviation, and superior performance in the model analysis. ConclusionThe comparative analysis methodology provides a systematic method to compare software tools and cameras for skeleton tracking. The ranking enables to prioritize different features. Skeleton tracking with the ZED cameras yielded better performances for both upper and lower extremities features.

bioengineering↗

bioRxiv2022

Age and cognitive load affect muscle activation profiles in response to physical perturbations while walking

To maintain balance during walking, the central nervous system must adjust the base of support (i.e., modulation of step length and step width) to the center of mass displacement in every step. We aimed to explore age and concurrent cognitive attention-demanding task effects on lower limb muscle fiber type recruitment in response to unexpected loss of balance during walking i.e., perturbation. Twenty young (YA) and 18 older adults (OA), (27.00{+/-}2.79 and 70.13{+/-}3.95 years old, respectively) were exposed to unexpected perturbations, while walking on a treadmill, in virtual reality environment. Surface electromyography (sEMG) total spectral power for frequency bands associated with muscle fibers type I (40-60Hz), type IIa (60-150Hz) and type IIb (150-250Hz), from tibialis-anterior and vastus-lateralis muscles were analyzed. Four Generalized Estimating Equations models assessed age and cognitive attention-demanding tasks load association with lower-limb muscle activation patterns resulting from perturbation in single- and double-support phases of the gait cycle. Results show that OA employ a muscle fiber type IIa dominant increase strategy while YA show muscle fiber type IIb dominant increase in muscle fiber type recruitment in response to unexpected perturbations during walking. This suggests that the ability to recruit fast-twitch muscle fibers is deteriorated with age and thus may be related to insufficient balance recovery response.

neuroscience↗

bioRxiv2021

Muscle Activation Profile While Walking with Perturbations

During an unexpected loss of balance, avoiding a fall requires people to readjust their footing rapidly and effectively. We investigated the activation patterns of the ankle and knee muscles, and muscle fiber type recruitment resulting from unannounced, medio-lateral (i.e., right/left) horizontal-surface walking perturbations in twenty healthy adults (27.00{+/-}2.79 years, 10 females). Surface electromyography (sEMG) total spectral power for specific frequency bands (40-60Hz, 60-150Hz, 150-250Hz, 250-400Hz and 400-1000Hz), from tibialis anterior (TA) and vastus lateralis (VL) muscles were analyzed. Compared to non-perturbed walking, we found a significant increase in the total spectral power of lower-extremity muscles during the first 3 seconds after perturbation. When two feet were on the ground in time of perturbation we found a different muscle fiber type recruitment pattern between VL and TA muscles. This was not significant for perturbations implemented when one foot was on the ground. Our findings suggest that muscle operating frequency is modulated in real time to fit body state and somatosensory input in the context of functional goal requirements such as a rapid change of footing in response to unexpected loss of balance in single and double-support phases of gait. New & NoteworthyTo study muscle spectral profiles in response to loss of balance, we investigated the dynamics of muscle spectral power changes, across different frequency bands after unannounced mechanical perturbations during walking. We showed increased activation of high-frequency motor units of the lower-limb muscles, subside 3 seconds after perturbation. Differences in power increase of specific frequency bands suggest that muscle activation is modulated in real time to fit body state in the context of functional goal requirements.

physiology↗

bioRxiv2019

Novel methodology for assessing total recovery time in response to unexpected perturbations while walking

Walking stability is achieved by adjusting the medio-lateral and anterior-posterior dimensions of the base of support (step length and step width, respectively) to contain an extrapolated center of mass. We aimed to calculate total recovery time after different types of perturbations during walking, and use it to compare young and older adults following different types of perturbations. Walking trials were performed in 12 young (age 26.92 {+/-} 3.40 years) and 12 older (age 66.83 {+/-} 1.60 years) adults. Perturbations were introduced at different phases of the gait cycle, on both legs and in anterior-posterior or medio-lateral directions, in random order. A novel algorithm was developed to determine total recovery time values for regaining stable step length and step width parameters following the different perturbations and compared between the two participant groups under low and high cognitive load conditions, using principal component analysis (PCA). We analyzed 829 perturbations each for step length and step width. The algorithm successfully estimated total recovery time in 91.07% of the runs. PCA and statistical comparisons showed significant differences in step length and step width recovery times between anterior-posterior and medio-lateral perturbations, but no age-related differences. Initial analyses demonstrated the feasibility of comparisons based on total recovery time calculated using our algorithm.

neuroscience↗