Normal Hand Movement Research Articles

Application of Artificial Neuromolecular System in Robotic Arm Control to Assist Progressive Rehabilitation for Upper Extremity Stroke Patients

Freedom of movement of the hands is the most desired hope of stroke patients. However, stroke recovery is a long, long road for many patients. If artificial intelligence can assist human arm movement, the possibility of stroke patients returning to normal hand movement might be significantly increased. This study uses the artificial neuromolecular system (ANM system) developed in our laboratory as the core of motion control, in an attempt to learn to control the mechanical arm to produce actions similar to human rehabilitation training and the transition between different activities. This research adopts two methods. The first is hypothetical exploration, the so-called “artificial world” simulation method. The detailed approach uses the V-REP (Virtual Robot Experimentation Platform) to conduct different experimental runs to capture relevant data. Our policy is to establish an action database systematically to a certain extent. From these data, we use the ANM system with self-organization and learning capabilities to develop the relationship between these actions and establish the possibility of conversion between different activities. The second method of this study is to use the data from a hospital in Toronto, Canada. Our experimental results show that the ANM system can continuously learn for problem-solving. In addition, our three experimental results of adaptive learning, transfer learning, and cross-task learning further confirm that the ANM system can use previously learned systems to complete the delivered tasks through autonomous learning (instead of learning from scratch).

Applying an Artificial Neuromolecular System to the Application of Robotic Arm Motion Control in Assisting the Rehabilitation of Stroke Patients-An Artificial World Approach.

Stroke patients cannot use their hands as freely as usual. However, recovery after a stroke is a long road for many patients. If artificial intelligence can assist human arm movement, it is believed that the possibility of stroke patients returning to normal hand movement can be significantly increased. In this study, the artificial neuromolecular system (ANM system) developed by our laboratory is used as the core motion control system to learn to control the mechanical arm, produce similar human rehabilitation actions, and assist patients in transiting between different activities. The strength of the ANM system lies in its ability to capture and process spatiotemporal information by exploiting the dynamic information processing inside neurons. Five experiments are conducted in this research: continuous learning, dimensionality reduction, moving problem domains, transfer learning, and fault tolerance. The results show that the ANM system can find out the arm movement trajectory when people perform different rehabilitation actions through the ability of continuous learning and reduce the activation of multiple muscle groups in stroke patients through the learning method of reducing dimensions. Finally, using the ANM system can reduce the learning time and performance required to switch between different actions through transfer learning.

A wearable and smart actuator for haptic stimulation

Wearable tactile technology in the configuration of actuated thimbles is used to provide the sense of touch in virtual (VR) and augmented reality (AR) and teleoperation contexts. The design of these types of devices includes specific purposes: limiting the overall dimensions of the system to enhance the wearability and increasing the effectiveness and naturalness of the stimulation. This new generation of wearable touch systems can transmit tactile signals more naturally, whilst also being comfortably worn by the user, portable and integrated in daily life. In this direction, we propose a haptic device based on electro-cutaneous feedback to selectively stimulate each mechanoreceptor to discriminate specific tactile sensations. Two important features characterize and make our device innovative: wearability and ease of use. The first feature is enhanced by a flexible holder made of a combination of polydimethylsiloxane (PDMS) and Kapton layers, that allows the device to be wrapped around the fingertip to provide stimulation in the area with higher density of mechanoreceptors and make possible to place the system ground close to the stimulus application point. A more complex stimulation enhances increasingly accurate tactile sensations, so the guidelines of our research were focused on the enrichment of parameters variety that define each stimulation (frequency, waveform, duty cycle, current intensity, anodic/cathodic configuration, and dynamic stimulation) by the development of a functional electronics board (4 h of autonomy per battery discharge cycle). The second feature uses the Bluetooth Low Energy (BLE) protocol to connect the electronic board of the device to a common smartphone, which allows user to manage the stimulation through a specific Android application allowing intelligent and integrated control of the haptic microsystem. Our haptic device is lightweight, does not affect normal hand movement, portable and easy to manage via your smartphone; this makes it available to a large scale of people. • Wearable tactile technology in the configuration of actuated thimbles. • Combination of the wearability and wireless skills in a single device. • The ability of suffering strains during its use without damaging own structure. • A design that doesn't affect the hand movement ensuring portability by smartphone. • Accessibility is enhanced by simplicity of use and wide diffusion of smartphones.

Integration of organic/inorganic nanostructured materials in a hybrid nanogenerator enables efficacious energy harvesting via mutual performance enhancement

Recent reports demonstrate that hybrid energy harvesting devices can efficiently convert ubiquitously available but mostly unexploited ambient energies (e.g., mechanical, chemical, thermal, solar) into usable power that can potentially support a new generation of self-powered electronic systems. In this paper, we present a hybrid organic/inorganic nanogenerator on shim substrates, which integrates both piezoelectric and triboelectric components based on inorganic p-n junction ZnO nanostructures and nanostructured organic polytetrafluoroethylene (PTFE) film, respectively. In this design, individual components can be operated independently or concurrently. Moreover, when operated concurrently, component performance is mutually enhanced, enabling more efficient conversion of mechanical energy into electrical energy in a single press-and-release cycle. When triggered with 25 Hz frequency and 1 G acceleration of external force, the piezoelectric nanogenerator (PENG) component generates a peak-to-peak output voltage of 34.8 V, which is ∼3 times higher than its output when it acts alone. Similarly, the triboelectric nanogenerator (TENG) component generates a peak-to-peak output voltage of 356 V under the same conditions, which is higher than its initial output of 280 V when acting alone. The nanogenerator unit produces an average peak output voltage of 186 V, current density of 10.02 µA/cm2, and average peak power density of 1.864 mW/cm2 when operated in the hybrid configuration. The device can even produce an average peak-to-peak voltage of ~160 V from normal hand movement when placed under a wristband fitness tracker, and ~580 V from human walking when placed within the walker's shoe. The device has been demonstrated to charge commercial capacitors up to a few volts within several seconds.

Reduced parietal activation in cervical dystonia after parietal TMS interleaved with fMRI

ObjectiveClinically normal hand movement with altered cerebral activation patterns in cervical dystonia (CD) may imply cerebral adaptation. Since impaired sensorimotor integration appears to play a role in dystonia, left superior parietal cortex modulation with repetitive transcranial magnetic stimulation (TMS) was employed to further challenge adaptation mechanisms reflected by changes in cerebral activation. MethodsSeven CD patients and ten healthy controls were scanned on a 3T magnetic resonance imaging (MRI) scanner with 1Hz inhibitory interleaved TMS. They executed and imagined right wrist flexion/extension movements. Each task was preceded by a 10-s period with or without TMS. ResultsThe activations of both tasks after TMS in controls showed a similar pattern as found in CD without TMS, i.e. activation increases in bilateral prefrontal and posterior parietal regions during both tasks and decreases in right anterior parietal cortex during imagery (P<0.001). the activations of both tasks after TMS in CD were weaker but with a similar trend in activation changes. Only in the right angular gyrus, TMS significantly failed to induce an activation increase in CD as was seen in the controls (P<0.001). ConclusionThe similarity between TMS effects on the distribution of cerebral activations in controls and the pattern seen in CD may support the concept that CD make use of compensatory circuitry enabling clinically normal hand movement. The fact that a similar but weaker TMS effect occurred in CD could suggest that the capacity of compensation is reduced. Particularly for the right angular gyrus, this reduction was statistically significant.

Changed patterns of cerebral activation related to clinically normal hand movement in cervical dystonia

Objectives The relief of cervical dystonia by sensory tricks points at complex sensorimotor interaction. The relation between such stimulus-induced normalization of posture and parietal activation [Naumann M, Magyar-Lehmann S, Reiners K, Erbguth F, Leenders KL. Sensory tricks in cervical dystonia: perceptual dysbalance of parietal cortex modulates frontal motor programming. Ann Neurol 2000;47:322–8] further supports the idea of disturbed higher-order motor control and suggests that the organization of movement is affected beyond the level of a local output channel. Dysbalance beyond a restricted output channel is also supported by the spread of focal dystonia to adjacent body parts. In this fMRI study, we aimed to determine whether cervical dystonia patients have indeed different patterns of cerebral activation during clinically normal hand performance. Patients and methods By means of statistical parametric mapping (SPM) of 3T fMRI results, task-related cerebral activations measured in eight cervical dystonia patients were compared to data of nine healthy volunteers. Results Compared to controls, the patient group showed a relative reduction of activations in bilateral parietal, left premotor and cingulate cortex regions during imagining of movement, while activation of right (ipsilateral) putamen, insula and cingulate cortex was impaired during movement execution. Conclusion Cervical dystonia appears to concern a general disorganization of cerebral motor control, which indicates a pre-dystonic state of clinically normal hand movements. The latter may imply an increased vulnerability for deteriorating triggers such as minor accidents.

Vision and kinesthesis in accuracy of hand movement.

Two experiments examined the accuracy with which college students were able to touch a target when knowledge of the target location had been gained either visually, kinesthetically, or by both modalities. In all but "baseline" trials, individuals were not allowed to guide the hand visually and so relied on kinesthetic cues during movement to the target location. No feedback was provided. Contrary to students' expectations, accuracy of the movements was greater when the target location had been given kinesthetically (passive movement to the target) as opposed to visually. When target location was provided by seeing one's hand move to the target (kinesthetic plus visual), performance was slightly poorer (though nonsignificantly) than for the purely kinesthetic condition, but significantly better than for a purely visual target condition. These results are discussed in terms of visual dominance and the roles of vision and kinesthesis in guiding normal hand movements.