Biology subjects

SKM, V.

Publications and source records attributed to SKM, V..

13 recordsLinked to original sources

bioRxiv2025

Mechanical advantage is not invoked by additional cognitive load during multi-finger dexterous object manipulation

Everyday interactions with objects depend on keeping the grasped item in static equilibrium by effectively distributing the contact forces from the fingertips. The mechanical advantage hypothesis (MAH) proposes that the central nervous system (CNS) optimises the distribution of grasping forces by favouring fingers with longer moment arms. While existing research has established that the applicability of MAH is influenced by biomechanical constraints, it remains unclear whether cognitive load, a distinct dimension of task difficulty, can similarly induce this force-sharing strategy. To investigate this, we examined whether increased cognitive demands during a multi-finger grasp- and-lift task would trigger force distribution patterns that exploit mechanical advantage. The results showed that while participants completed the task successfully, contrary to our hypothesis, the increased cognitive load did not result in a disproportionate rise in the normal force exerted by the little finger compared to the ring finger. This finding suggests that the employment of optimisation strategies like mechanical advantage may be predominantly sensitive to biomechanical rather than cognitive constraints. Significance StatementHuman grasping is a redundant control problem in that the hand has more ways to produce forces and moments than are strictly needed to achieve desired object interaction. The mechanical advantage hypothesis (MAH) is an optimisation principle proposing that the central nervous system (CNS) prefers fingers with greater leverage to address this redundancy during object manipulation. While MAH is known to emerge when mechanical difficulty increases, this study probes its boundaries and generality by asking whether nonmechanical demands also trigger it. The findings show that increased cognitive demand does not invoke MAH, highlighting that this optimisation arises primarily in response to physical and biomechanical task demands, with implications for dexterous control in rehabilitation, assistive technology, and robotics.

animal behavior and cognition↗

bioRxiv2024

Comparable neural and behavioural performance in dominant and non-dominant hands during grasping tasks

Hand dominance has long been associated with differences in neural control and motor performance, with the dominant hand typically exhibiting better coordination in reaching tasks. However, the extent to which this dominance influences performance in finger force control remains unclear. This study aimed to examine the behavioural and neural features of the dominant and non-dominant hands during grasping and lifting tasks in healthy young adults, focusing on the synergy index, EEG band power, and EEG-EMG coherence as key measures. Twenty right-handed adults (mean age = 26.95, STD = 2.68) participated in this study. Participants engaged in an experimental task where they grasped a handle for the initial five seconds, followed by lifting and holding it for an additional five seconds. There were two task conditions: fixed (thumb platform secured) and free (thumb platform movable). They performed 25 trials with both the dominant and non-dominant hands in the two task conditions, with the order of trials and hands block randomized to eliminate potential order effects. Contrary to the dynamic dominance hypothesis, we found statistical equivalence in the synergy index, EEG band power, and EEG-EMG coherence between the dominant and non-dominant hands across both fixed and free task conditions. These findings suggest that both hands are capable of achieving similar levels of performance in tasks emphasizing steady-state force maintenance, despite the typical advantages of the dominant hand in other motor tasks. While task-dependent modulations in behavioural and neural features were observed due to changes in friction, these adjustments were non-different between the dominant and non-dominant hands.

neuroscience↗

bioRxiv2024

Older individuals do not show task specific variations in EEG band power and finger force coordination

BackgroundControlling and coordinating finger force is crucial for performing everyday tasks and maintaining functional independence. Aging naturally weakens neural, muscular, and musculoskeletal systems, leading to compromised hand motor function. This decline reduces cortical activity, finger force control and coordination in older adults. ObjectiveTo examine the relationship between EEG band power and finger force coordination in older individuals and compare the results with young adults. MethodsTwenty healthy young adults aged 20-30 (26.96{+/-}2.68) and fourteen older adults aged 58-72 (62.57{+/-}3.58) participated in this study. Participants held the instrumented handle gently for five seconds then lifted and held it for an additional five seconds in the two conditions: fixed (thumb platform secured) and free condition (thumb platform may slide on slider). ResultsIn the older individuals there was no difference observed in the finger force synergy indices, and EEG beta band power between the two task conditions. However, in the young group synergy indices and EEG beta band power were less in free condition compared to fixed condition. Additionally, in the fixed condition, older adults showed a reduced synergy indices and reduced EEG beta band power than the young adults. ConclusionOlder participants showed consistent synergy indices and beta band power across conditions, unlike young adults who adjusted strategies based on tasks. Young adults exhibited task-dependent finger force synergy indices contrasting with older individuals. These results suggest that the EEG beta band power may serve as a marker for finger force coordination rather than indicating the magnitude of force.

neuroscience↗

bioRxiv2024

Grasp context-dependent uncertainty alters the relative contribution of anticipatory and feedback-based mechanisms in object manipulation

Predictive control within dexterous object manipulation while allowing for the choice of contact points has been shown to employ a predominantly feedback-based force modulation. Anticipation is thought to be facilitated through the internal representation of the object dynamics being integrated and updated on a trial-to-trial basis with the feedback of contact locations on the object. This is as opposed to the classically studied memory representation-based fingertip force control for grasping with pre-selected contact locations. We designed a study to examine this grasp context-dependent asymmetry in sensorimotor integration by introducing binary uncertainty about the grasp type before movement initiation within the framework of motor planning. An inverted T-shaped instrumented object was presented to 24 participants as the manipulandum, and they were asked to reach, grasp, and lift it while minimising the roll. We dissociated the planning and the execution phases by pseudo-randomly manipulating the availability of visual contact cues on the object after movement onset. Our results suggest that uncertainty about the grasp type during movement preparation anterogradely modulated the differential weighting of feedback and feedforward mechanisms in anticipatory coordination.

neuroscience↗

bioRxiv2023

Internal feedback enables rapid trajectory control during goal-directed finger and whole-arm reaching movements

Goal-directed eye, hand, and finger movements follow invariant kinematics consisting of approximate straight-line trajectories and bell-shaped velocity profiles. A fundamental unresolved issue is whether these trajectories are planned or whether they are a consequence of trajectory-free online control. We address this question using Spearmans rank correlation, zero-crossing rate, and z-scores, and analyze within-trial variability to investigate differences in the time evolution of trajectories during the presence or absence of a goal in finger and whole-arm reaching movements, along with analyzing rapid goal-directed saccadic eye movements. We found that the central nervous system (CNS) implements control to follow an average trajectory, where goal-directed movements show an enhanced degree of trajectory control. Further, we found behavioral signatures of rapid control that might operate on these planned trajectories as early as [~]60 ms in finger movements and [~]70 ms in whole-arm reaching movements. Such early signatures of control suggest that the system could exploit internal feedback along with fast feedback processes to implement meaningful corrections during simple voluntary unperturbed movements. The analysis also revealed that the controller gains varied along the movement and peaked distinctly at early (20 %) and late (90 %) phases of finger and arm movements, implying that trajectory control may be accomplished through implicit way-point objectives during the execution of the movement. These later corrections were missing during the late phase of eye movements, pointing to a predominant role of delayed sensory feedback mediating corrections in the context of finger and arm movements during this period.

neuroscience↗

bioRxiv2022

Comparing algorithms for assessing upper limb use with inertial measurement units

The various existing measures to quantify upper limb use from wrist-worn inertial measurement units (IMU) can be grouped into three categories: (a) Thresholded activity counting, (b) Gross movement score and (c) machine learning. While machine learning algorithms are a promising approach to detect upper limb use, there is currently no knowledge of the information used by these methods, and the data-related factors that influence their performance. A comparison of existing methods was carried out using data from a previous study which was collected from 10 unimpaired and 5 hemiparetic subjects, with annotation to identify periods of functional and non-functional upper limb use. Intra-subject random forest machine learning measures were found to classify upper limb use more accurately than other measures. The random forest measure uses information about the orientation and the amount of movement of the forearm to detect upper limb use. The types of movements and the proportion of functional data included in training/testing set influences the performance of machine learning measures. This study presents the first step towards understanding and optimizing machine learning methods for upper limb use assessment using wearable sensors.

bioengineering↗

bioRxiv2021

Distinct behavior of the little finger during the vertical translation of an unsteady thumb platform while grasping

Object stabilization while grasping is a common topic of research in motor control and robotics. Forces produced by the peripheral fingers (index and little) play a crucial role in sustaining the rotational equilibrium of a handheld object. In this study, we examined the contribution of the peripheral fingers towards object stabilization when the rotational equilibrium is disturbed. For this purpose, the thumb was placed over an unsteady platform and vertically translated. The task was to trace a trapezoid or an inverted trapezoid pattern by moving the thumb platform in the vertical direction. The thumb displacement data served as visual feedback to trace the pattern displayed. Participants were instructed to maintain the handle in static equilibrium at all times. We observed that the change in the normal force of the little finger due to the downward translation of the thumb was significantly greater than the change in the normal force of the index finger due to the upward translation. We speculate that morphological correlations (between thumb and little finger) during the displacement of the thumb might be a reason for such large increases in the little finger forces.

neuroscience↗

bioRxiv2021

A Framework for Sensor-based Assessment of Upper-limb Functioning

AO_SCPLOWBSTRACTC_SCPLOWThe ultimate goal of any upper-limb neurorehabilitation procedure is to improve upper-limb functioning in daily life. While clinic-based assessments provide an assessment of what a patient can do, they do not completely reflect what a patient does in his/her daily life. The compensatory use of the less affected upper-limb (e.g. "learned non-use") in daily life is a common behavioral pattern seen in patients with hemiparesis. To this end, there has been an increasing interest in the use of wearable sensors to objectively assess upper-limb functioning. This paper presents a framework for assessing upper-limb functioning using sensors by providing: (a) a set of definitions of important construct associated with upper-limb functioning; (b) presenting different visualization methods for evaluating upper-limb functioning, along ways to qualitatively analyze different visualization methods; and (c) two new measures for quantifying how much an upper-limb is used and the relative bias in the use of the two upper-limbs. The demonstration of some of these components is presented using data collected from inertial measurement units from a previous study. The proposed framework can help guide the future technical and clinical work in this area to realize a valid, objective, and robust tool for assessing upper-limb functioning. This will in turn drive the refinement and standardization of the assessment of upper-limb functioning.

bioengineering↗

bioRxiv2020

Practice modifies the response to errors during a novel motor sequence learning task

The occurrence of an error when performing a motor sequence causes an immediate reduction in speed on subsequent trials, which is referred to as post-error slowing. However, understanding how post-error slowing changes with practice has been difficult because it requires extended practice on a novel sequence task. To address this issue, we examined post-error slowing in a novel glove-based typing task that participants performed for 15 consecutive days. Speed and accuracy improved from the early to middle stages of practice, but did not show any further improvements between middle and late stage of practice. However, when we analyzed the response to errors, we found that participants decreased both the magnitude and duration of post-error slowing with practice, even after there were no detectable improvements in overall task performance. These results indicate that learning not only improves overall task performance but also modifies the ability to respond to errors.

neuroscience↗

bioRxiv2020

A test of the mechanical advantage hypothesis during artificial reduction in thumb contribution to hold objects

BackgroundThe human hand plays a crucial role in accomplishing activities of daily living. The contribution of each finger in the human hand is remarkably unique in establishing object stabilization. According to the mechanical advantage hypothesis, the little finger tends to exert a greater normal force than the ring finger during a supination moment production task to stabilize the object. Similarly, during pronation, the index finger produces more normal force when compared with the middle finger. Hence, the central nervous system employs the peripheral fingers for torque generation to establish the equilibrium as they have a mechanical advantage of longer moment arms for normal force. In our study, we tested whether the mechanical advantage hypothesis is supported in a task in which the contribution of thumb was artificially reduced. We also computed the safety margin of the individual fingers and thumb. MethodologyFifteen participants used five-finger prismatic precision grip to hold a custom-built handle with a vertical railing on the thumb side. A slider platform was placed on the railing such that the thumb sensor could move either up or down. There were two experimental conditions. In the "Fixed" condition, the slider was mechanically fixed, and hence the thumb sensor could not move. In the "Free" condition, the slider platform on which the thumb sensor was placed could freely move. In both conditions, the instruction was to grasp and hold the handle (and the platform) in static equilibrium. We recorded tangential and normal forces of all the fingers. ResultsThe distribution of fingertip forces and moments changed depending on whether the thumb platform was movable (or not). In the free condition, the drop in the tangential force of thumb was counteracted by an increase in the normal force of the ring and little finger. Critically, the normal forces of the ring and little finger were statistically equivalent. The safety margin of the index and middle finger did not show a significant drop in the free condition when compared to fixed condition. ConclusionWe conclude that our results does not support the mechanical advantage hypothesis at least for the specific mechanical task considered in our study. In the free condition, the normal force of little finger was comparable to the normal force of the ring finger. Also, the safety margin of the thumb and ring finger increased to prevent slipping of the thumb platform and to maintain the handle in static equilibrium during the free condition. However, the rise in the safety margin of the ring finger was not compensated by a drop in the safety margin of the index and middle finger.

neuroscience↗

bioRxiv2019

Role of post-trial visual feedback on unintentional force drift during isometric finger force production tasks

Force produced during an isometric finger force production task tends to drift towards a lower magnitude when visual information is occluded. This phenomenon of drift in force without ones awareness is called unintentional drift. The present study used epilogue, a particular case of post-trial visual feedback, and compared the unintentional drift for two conditions, i.e., with and without the epilogue. For this purpose, fourteen healthy participants were recruited for the experiments and were instructed to produce fingertip forces using four fingers of the right hand with the target line at 15% MVC. A trial lasted for sixteen seconds, where for the initial eight seconds, there is visual feedback followed by the visual occlusion period. The results showed a significant reduction in unintentional drift for the condition involving epilogue when compared to no epilogue. This reduction in drift is due to the shift in the referent configuration parameter by the phenomenon of RC back coupling. Further, we also claim that there might be a distribution of {lambda}s or RCs, based on the history of tuning of the control parameter by the central controller. This distribution of {lambda}s selected by the central controller in a redundant environment based on the epilogue resulted in a reduction of unintentional drift.

neuroscience↗

bioRxiv2017

Effort distribution changes effector choice, behaviour and performance: A visuomotor tracking study using finger forces

Human movement and its associated performance are bounded by a hierarchy of constraints operating over certain control variables. One such variable of both physiological and behavioural importance is the mechanical effort exerted by the participating elements. Here, we explored how motor performance is affected by the distribution of work, and consequently the effort.\n\nUsing human hand as a model, we employed a visuomotor tracking task to study the associated motor performance when mechanical effort exerted by the fingers are modulated. The subject has to trace a set of ideal paths provided on visual feedback screen to reach a target through a cursor controlled by index and little finger forces. Modulation of these forces allows us to see how the perceived effort requirement affects the tracking performance. In this task demanding two-element coordination, we represent index finger as the independent/dominant element against little finger as the dependent/subjugate counterpart. We study how increasing mechanical effort contribution from the independent element leads to changes in both behaviour and performance.\n\nWe found that despite higher mechanical requirements of employing index finger to produce larger absolute force, the movement control system continues to prefer it as against little finger which could have produced smaller absolute force. Moreover, the observation of better tracking performance under larger contributions from the independent component reflects to a plausible hierarchy of constraints employed in the motor control system that operates with more than one objective, energy minimisation per se. At least for the behaviour in study, the improved motor performance suggests that the control system prefers higher independence of the participating elements.

neuroscience↗

bioRxiv2017

Sensor location optimization and joint angle prediction in hand postures

1. Sensor selection problem 1. Sensor selection problem Grasping of objects (Mason et al. 2001; Santello et al. 2002) or hand shaping during grasping is of interest in robotics, neuroscience, and biomechanics. In animation industry and biomechanics, tracking body and hand movements are essential. For tracking body movements and hand movements, a sizable number of markers are required. As number of marker increase complexity and cost also increase. Researchers have tried various approaches for selecting a set of minimum no. of markers for accurate reproduction of movements. Data-driven approaches have been proposed for classification of various grasps. Some studies have focussed on prediction of joint angles (Kang et al. 2012; Hoyet et al. 2012; Wheatland et al. 2013). Our objective is to predict joint angles from a reduced set of sensors. For preliminary sorting purpose, we used PCA based sensor ranking which is disc ...

bioengineering↗