Analysis of subject specific grasping patterns

Does Exerting Grasps Involve a Finite Set of Muscle Patterns? A Study of Intra- and Intersubject Variability of Forearm sEMG Signals in Seven Grasp Types

Surface Electromyography (sEMG) signals are widely used as input to control robotic devices, prosthetic limbs, exoskeletons, among other devices, and provide information about someone's intention to perform a particular movement. However, the redundant action of 32 muscles in the forearm and hand means that the neuromotor system can select different combinations of muscular activities to perform the same grasp, and these combinations could differ among subjects, and even among the trials done by the same subject. In this work, 22 healthy subjects performed seven representative grasp types (the most commonly used). sEMG signals were recorded from seven representative forearm spots identified in a previous work. Intra- and intersubject variability are presented by using four sEMG characteristics: muscle activity, zero crossing, enhanced wavelength and enhanced mean absolute value. The results confirmed the presence of both intra- and intersubject variability, which evidences the existence of distinct, yet limited, muscle patterns while executing the same grasp. This work underscores the importance of utilizing diverse combinations of sEMG features or characteristics of various natures, such as time-domain or frequency-domain, and it is the first work to observe the effect of considering different muscular patterns during grasps execution. This approach is applicable for fine-tuning the control settings of current sEMG devices.

Force Control Strategy of Five-Digit Precision Grasping With Aligned and Unaligned Configurations

OBJECTIVE

To investigate the digit force control during a five-digit precision grasp in aligned (AG) and unaligned grasping (UG) configurations.

BACKGROUND

The effects of various cylindrical handles for tools on power grasp performance have been previously investigated. However, there is little information on force control strategy of precision grasp to fit various grasping configurations.

METHOD

Twenty healthy young adults were recruited to perform a lift-hold-lower task. The AG and UG configurations on a cylindrical simulator with force transducers were adjusted for each individual. The applied force and moment, the force variability during holding, and force correlations between thumb and each finger were measured.

RESULT

No differences in applied force, force correlation, repeatability, and variability were found between configurations. However, the moments applied in UG were significantly larger than those in AG.

CONCLUSION

The force control during precision grasp did not change significantly across AG and UG except for the digit moment. The simulator is controlled efficiently with large moment during UG, which is thus the optimal configuration for precision grasping with a cylindrical handle. Further research should consider the effects of task type and handle design on force control, especially for individuals with hand disorders.

APPLICATION

To design the handle of specific tool, one should consider the appropriate configuration according to the task requirements of precision grasping to reduce the risk of accumulating extra loads on digits with a cylindrical handle.

A pediatric seizure management virtual reality simulator for nursing students: A quasi-experimental design

BACKGROUND

Seizures are a common neurologic disorder observed in children. A virtual reality (VR) simulator trains nursing students to understand and respond to pediatric seizures.

OBJECTIVES

The aim of this study was to examine knowledge acquisition and acceptance of a pediatric seizure management VR simulator.

DESIGN

A quasi-experimental design was used to study the effectiveness of VR in nursing education.

PARTICIPANTS

Two out of nine possible third-year Pediatric Nursing classes were assigned by the office of academic affairs. A total of 105 students participated. The two classes were randomly allocated into the intervention (n = 53) and control (n = 52) groups.

METHODS

The intervention group was taught using a pediatric seizure management simulator; the control group was taught by in-person lecture. The Seizure Management Knowledge Test was administered to all participants before each group underwent their VR simulator and lecture respectively. The Pediatric Seizure Management Virtual Reality Acceptance Questionnaire and the Virtual Reality Sickness Questionnaire were given to participants in the intervention group. Independent t-tests and chi-square tests were used to test differences in knowledge acquisition between the two groups.

RESULTS

The posttest knowledge score in the intervention group was significantly higher than that in the control group (t = 5.05, p < .001). The intervention group had a mean cybersickness score of 18.17 of 100. The average score of the acceptance questionnaire for perceived usefulness was 3.26 of 4; ease of use was 3.09 of 4; attitude toward use was 3.26 of 4; and willingness to use was 3.32 of 4. Over 90 % of participants expressed willingness to use the VR simulator.

CONCLUSIONS

The newly developed pediatric seizure management VR simulator is acceptable and worthwhile for training nursing students to develop their skills and professionalism. Follow-up research is needed to evaluate the long-term effect of VR education in nursing practice.

Analytical-stochastic model of motor difficulty for three-dimensional manipulation tasks

Multiple models exist for the evaluation of human motor performance; some of these rely on the Index of Difficulty (ID), a measure to evaluate the difficulty associated to simple reaching tasks. Despite the numerous applications of the ID in reaching movements, the existing formulations are functions of the geometrical features of the task and do not consider the motor behaviour of subjects performing repetitive movements in interaction with the environment. Variability of movements, length of trajectories, subject-specific strength and skill, and required interaction with the environment are all factors that contribute to the motor difficulty experienced by a moving agent (e.g., human, robot) as it repeatedly interacts with the environment during a given task (e.g., target-reaching movement, locomotion, etc.). A novel concept of motor difficulty experienced by an agent executing repetitive end-effector movements is presented in this study. A stochastic ID formulation is proposed that captures the abovementioned factors and applies to general three-dimensional motor tasks. Natural motor variability, inherent in the proposed model, is representative of the flexibility in motor synergies for a given agent-environment interaction: the smaller the flexibility, the greater the experienced difficulty throughout the movement. The quantification of experienced motor difficulty is demonstrated for the case of young healthy subjects performing three-dimensional arm movements during which different objects are manipulated. Results show that subjects’ experienced motor difficulty is influenced by the type of object. In particular, a difference in motor difficulty is observed when manipulating objects with different grasp types. The proposed model can be employed as a novel tool to evaluate the motor performance of agents involved in repetitive movements, such as in pick and place and manipulation, with application in both industrial and rehabilitation contexts.