On the Design and Development of a Zigbee-Based Multimodal Input-Output Monitoring-Actuating System

The monitoring of a physically challenged patient’s activities is a crucial and difficult task for the medical professionals. The design and development of a multimodal- input and output wireless system with two sensors and three actuators that can be used for just monitoring or for both monitoring and stimulating are discussed in this research. Touch and tilt sensors at the input part of the system attached to Zigbee modules communicate in a wireless manner with voice, vibration and light actuators connected to Zigbee modules at the output part. The hardware and the software parts are designed and integrated in such a way that a new sensor at the input or a new actuator at the output can be included or excluded based on the needs of the patient. It is shown how to design and develop sensors. In an application programming interface communication mode, 3 XBee series 1 modules send and receive data in a wireless manner. The prototype of the system was tested with promising results in the case of the patients with inattention disorder. This system can be used for monitoring the activities of a patient and also for actuating certain stimulus in the patient side in case of necessity

Three Patterns Programmable Russian Form Functional Electrical Stimulator

In this paper, a programmable, multi-pattern, wide frequency and duty cycle range electrical stimulator is presented. Using a programmable micro-controller, two waves of carrier and modulating sources are produced. By modulating the two sources, 3 bi-phasic charge-balanced rectangular, triangular and sinusoidal stimulating patterns are produced. The frequency range of the carrier is fixed at 2.5 kHz and the carrier source frequency can be adjusted between 1 and 500 Hz. The duty cycle of both sources can be adjusted between 10% and 90%

Effect of Sensory Loss on Improvements of Upper-Limb Paralysis Through Robot-Assisted Training : A Preliminary Case Series Study

Sensory disorder is a factor preventing recovery from motor paralysis after stroke. Although several robot-assisted exercises for the hemiplegic upper limb of stroke patients have been proposed, few studies have examined improvement in function in stroke patients with sensory disorder using robot-assisted training. In this study, the efficacies of robot training for the hemiplegic upper limb of three stroke patients with complete sensory loss were compared with those of 19 patients without complete sensory loss. Robot training to assist reach motion was performed in 10 sessions over a 2-week period for 5 days per week at 1 h per day. Before and after the training, the total Fugl–Meyer Assessment score excluding coordination and tendon reflex (FMA-total) and the FMA shoulder and elbow score excluding tendon reflex (FMA-S/E) were evaluated. Reach and patherrors (RE and PE) during the reach motion were also evaluated by the arm-training robot. In most cases, both the FMA-total and the FMA-S/E scores improved. Cases with complete sensory loss showed worse RE and PE scores. Our results suggest that motor paralysis is improved by robot training. However, improvement may be varied according to the presence or absence of somatic sensory feedback. © 2019 MDPI (Basel, Switzerland).Funders: Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) &amp; Japan Society for the Promotion of Science &amp; Grants-in-Aid for Scientific Research (KAKENHI) (Grant numbers JP 15H05359 and 16K01524).</p

Bilateral Tactile Feedback-Enabled Training for Stroke Survivors Using Microsoft KinectTM

Rehabilitation and mobility training of post-stroke patients is crucial for their functional recovery. While traditional methods can still help patients, new rehabilitation and mobility training methods are necessary to facilitate better recovery at lower costs. In this work, our objective was to design and develop a rehabilitation training system targeting the functional recovery ofpost-stroke users with high efficiency. To accomplish this goal, we applied a bilateral training method, which proved to be effective in enhancing motor recovery using tactile feedback for the training. One participant with hemiparesis underwent six weeks of training. Two protocols, “contralater alarm matching” and “both arms moving together”, were carried out by the participant. Each ofthe protocols consisted of “shoulder abduction” and “shoulder flexion” at angles close to 30 and 60 degrees. The participant carried out 15 repetitions at each angle for each task. For example, in the“contralateral arm matching” protocol, the unaffected arm of the participant was set to an angle close to 30 degrees. He was then requested to keep the unaffected arm at the specified angle while trying to match the position with the affected arm. Whenever the two arms matched, a vibration was given on both brachialis muscles. For the “both arms moving together” protocol, the two arms were first set approximately to an angle of either 30 or 60 degrees. The participant was asked to return both arms to a relaxed position before moving both arms back to the remembered specified angle.The arm that was slower in moving to the specified angle received a vibration. We performed clinical assessments before, midway through, and after the training period using a Fugl-Meyer assessment (FMA), a Wolf motor function test (WMFT), and a proprioceptive assessment. For the assessments, two ipsilateral and contralateral arm matching tasks, each consisting of three movements (shoulder abduction, shoulder flexion, and elbow flexion), were used. Movements were performed at two angles, 30 and 60 degrees. For both tasks, the same procedure was used. For example, in the case of the ipsilateral arm matching task, an experimenter positioned the affected arm of the participant at 30 degrees of shoulder abduction. The participant was requested to keep the arm in that positionfor ~5 s before returning to a relaxed initial position. Then, after another ~5-s delay, the participant moved the affected arm back to the remembered position. An experimenter measured this shoulder abduction angle manually using a goniometer. The same procedure was repeated for the 60 degree angle and for the other two movements. We applied a low-cost Kinect to extract the participant’s body joint position data. Tactile feedback was given based on the arm position detected by the Kinect sensor. By using a Kinect sensor, we demonstrated the feasibility of the system for the training ofa post-stroke user. The proposed system can further be employed for self-training of patients at home. The results of the FMA, WMFT, and goniometer angle measurements showed improvements in several tasks, suggesting a positive effect of the training system and its feasibility for further application for stroke survivors’ rehabilitation. © 2019 by the authors.Funder: Canadian Institutes of Health Research (CIHR), (Grant Number: 353444)</p