Biology subjects

Ahmadabadi, M. N.

Publications and source records attributed to Ahmadabadi, M. N..

4 recordsLinked to original sources

bioRxiv2022

Effects of Reduced Achilles Subtendons Relative Displacement on Healthy Elderly Walking: A Simulation Study

Walking in healthy elderly people is characterized by lower performance. Since conventional training programs have had limited success in improving gait performance, it is essential to identify underlying causes of walking deficits in healthy elderly adults. Recent studies have qualitatively shown that the decreased relative displacement of Achilles subtendons is likely the primary contributor to lower propulsion in the elderlys walking by creating a higher dependency on their triceps-surae muscle functions. Due to the invasive nature of experimental investigations, in this study, we developed a computational model and analyzed the effects of reduced Achilles subtendons relative displacement on the total metabolic rate and muscles force profiles during normal walking. Our musculoskeletal simulations revealed a 17% increase in the total metabolic rate in elderly adults whose Achilles subtendons were restricted to have no relative displacement. Changing the restriction level resulted in significant changes in the force distribution of the plantar flexor muscles, notably, a 40% reduction in the Medial Gastrocnemius and a 124% increase in the Soleus forces during the propulsion phase of walking. Also, we quantitatively presented the higher dependency of triceps-surae muscle functions regarding the limitation on their corresponding Achilles subtendons relative displacement. The results of this study confirm the experimental observations and can be used as initial insight into devising novel rehabilitation training programs with the focus on improving Achilles subtendons relative displacement.

bioengineering↗

bioRxiv2020

Human-in-the-Loop Weight Compensation and Mass Estimation in Upper Limb Wearable Robots Towards Muscles Effort Minimization

In this paper: (1) We present a novel human-in-the-loop adaptation method for whole arm muscles effort minimization by means of weight compensation in the face of an object with an unknown mass. (2) This adaptation rule can also be used as a cognitive model for the identification of mass value using EMG sensors. (3) This adaptation rule utilizes the activation (myoelectric) signal of only four muscles in the upper limb to minimize the whole muscles effort. We analytically discuss the stability, optimality, and convergence of the proposed method. The effectiveness of this method for whole muscles effort reduction is studied by simulations (OpenSim software) on a generic and realistic model of the human arm, a model with 7-DOF and 50 Hill-type-muscles. The simulation results show the presented methods performance and applicability for weight compensation and mass estimation in upper limb assistive robots. In addition, the simulations in OpenSim completely support that the suggested set of mono-articular muscles are sufficient for whole muscles effort reduction.

bioengineering↗

bioRxiv2020

A Kinematic Index for Estimation of Metabolic Rate Reduction in Running with I-RUN

In this paper, we target multiple goals related to our passive running assistive device, called I-RUN. The major goals are: (1) finding the main reason behind individual differences in benefiting from our assistive device at the muscles level, (2) devising a simple measure for on-line I-RUN stiffness tuning, and creating a lab-free simple kinematic measure for (3) estimating metabolic rate reduction as well as (4) training subjects to maximize their benefit from I-RUN. Our approach is using some extensive data-driven OpenSim simulation results employing a generic lower limb model with 92-muscles and 29-DOF. It is observed that there is a significant relation between the hip joints kinematic and changes in the metabolic rate in the presence of I-RUN. Accordingly, a simple kinematic index is devised to estimate metabolic rate reduction. This index not only explains individual differences in metabolic rate reduction but also provides a quantitative measure for training subjects to maximize their benefits from I-RUN. The simulation results also re-confirm our hypothesis that "reducing the forces of two antagonistic mono-articular muscles is sufficient for involved muscles total effort reduction". Consequently, we introduce a two-muscles EMG-based metric for the on-line tuning of I-RUN.

bioengineering↗

bioRxiv2020

Learning to Integrate an Artificial Sensory Device: From Decision Fusion to Sensory Integration

The present study examines how artificial tactile stimulation from a novel non-invasive sensory device is learned and integrated with information from another sensory system. Participants were trained to identify the direction of visual dot motion stimuli with a low, medium, and high signal-to-noise ratio. In bimodal trials, this visual direction information was paired with reliable symbolic tactile information. Over several training blocks, discrimination performance in unimodal tactile test trials and subjects confidence in their decision improved, indicating that participants were able to associate the visual and tactile information consciously and thus learned the meaning of the symbolic tactile cues. Formal analysis of the results in bimodal trials showed that both modalities are being integrated already in the early learning phases. Our modeling results revealed that this integration is consistent with a Bayesian model, which is an optimal integration of sensory information. Furthermore, we showed that a confidence-based Bayesian integration explains the observed behavioral data better than the classical variance-based Bayesian integration. Thus, the present study demonstrates that humans can consciously learn and integrate an artificial sensory device that delivers symbolic tactile information. This finding connects the field of multisensory integration research to the development of sensory substitution systems.

neuroscience↗