Showing papers by "Ernest Nlandu Kamavuako published in 2021"

Affordable Embroidered EMG Electrodes for Myoelectric Control of Prostheses: A Pilot Study.

Abstract: Commercial myoelectric prostheses are costly to purchase and maintain, making their provision challenging for developing countries. Recent research indicates that embroidered EMG electrodes may provide a more affordable alternative to the sensors used in current prostheses. This pilot study investigates the usability of such electrodes for myoelectric control by comparing online and offline performance against conventional gel electrodes. Offline performance is evaluated through the classification of nine different hand and wrist gestures. Online performance is assessed with a crossover two-degree-of-freedom real-time experiment using Fitts' Law. Two performance metrics (Throughput and Completion Rate) are used to quantify usability. The mean classification accuracy of the nine gestures is approximately 98% for subject-specific models trained on both gel and embroidered electrode offline data from individual subjects, and 97% and 96% for general models trained on gel and embroidered offline data, respectively, from all subjects. Throughput (0.3 bits/s) and completion rate (95-97%) are similar in the online test. Results indicate that embroidered electrodes can achieve similar performance to gel electrodes paving the way for low-cost myoelectric prostheses.

Software Sensor to Enhance Online Parametric Identification for Nonlinear Closed-Loop Systems for Robotic Applications

Abstract: This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.

Altered evoked low-frequency connectivity from SI to ACC following nerve injury in rats.

Abstract: Objective. Despite decades of research on central processing of pain, there are still several unanswered questions, in particular regarding the brain regions that may contribute to this alerting sensation. Since it is generally accepted that more than one cortical area is responsible for pain processing, there is an increasing focus on the interaction between areas known to be involved.Approach. In this study, we aimed to investigate the bidirectional information flow from the primary somatosensory cortex (SI) to the anterior cingulate cortex (ACC) in an animal model of neuropathic pain.19 rats (nine controls and ten intervention) had an intracortical electrode implanted with six pins in SI and six pins in ACC, and a cuff stimulation electrode around the sciatic nerve. The intervention rats were subjected to the spared nerve injury (SNI) after baseline recordings. Electrical stimulation at three intensities of both noxious and non-noxious stimulation was used to record electrically evoked cortical potentials. To investigate information flow, two connectivity measures were used: phase lag index (PLI) and granger prediction (GP). The rats were anesthetized during the entire study.Main results. Immediately after the intervention (<5 min after intervention), the high frequency (γandγ+) PLI was significantly decreased compared to controls. In the last recording cycle (3-4 h after intervention), the GP increased consistently in the intervention group. Peripheral nerve injury, as a model of neuropathic pain, resulted in an immediate decrease in information flow between SI and ACC, possibly due to decreased sensory input from the injured nerve. Hours after injury, the connectivity between SI and ACC increased, likely indicating hypersensitivity of this pathway.Significance. We have shown that both a directed and non-directed connectivity between SI and ACC approach can be used to show the acute changes resulting from the SNI model.

Online Closed-Loop Control Using Tactile Feedback Delivered Through Surface and Subdermal Electrotactile Stimulation.

Abstract: Aim Limb loss is a dramatic event with a devastating impact on a person's quality of life. Prostheses have been used to restore lost motor abilities and cosmetic appearance. Closing the loop between the prosthesis and the amputee by providing somatosensory feedback to the user might improve the performance, confidence of the amputee, and embodiment of the prosthesis. Recently, a minimally invasive method, in which the electrodes are placed subdermally, was presented and psychometrically evaluated. The present study aimed to assess the quality of online control with subdermal stimulation and compare it to that achieved using surface stimulation (common benchmark) as well as to investigate the impact of training on the two modalities. Methods Ten able-bodied subjects performed a PC-based compensatory tracking task. The subjects employed a joystick to track a predefined pseudorandom trajectory using feedback on the momentary tracking error, which was conveyed via surface and subdermal electrotactile stimulation. The tracking performance was evaluated using the correlation coefficient (CORR), root mean square error (RMSE), and time delay between reference and generated trajectories. Results Both stimulation modalities resulted in good closed-loop control, and surface stimulation outperformed the subdermal approach. There was significant difference in CORR (86 vs 77%) and RMSE (0.23 vs 0.31) between surface and subdermal stimulation (all p < 0.05). The RMSE of the subdermal stimulation decreased significantly in the first few trials. Conclusion Subdermal stimulation is a viable method to provide tactile feedback. The quality of online control is, however, somewhat worse compared to that achieved using surface stimulation. Nevertheless, due to minimal invasiveness, compactness, and power efficiency, the subdermal interface could be an attractive solution for the functional application in sensate prostheses.