Walking Foot Insoles for Dynamic Postural Analysis of Patients with Gait Imbalance: A Preliminary Report

There are different cycles involved in the gait. In order to detect the pathological gait, it is necessary to understand the normal gait. During walk, various parameters were calculated to do analysis for providing further gait training. The aim of this study is to do the investigation and precise identification of deviation in gait pattern. Experimental study is done on thirty-one test subjects suffering from gait impairment. Further, data analysis on subjects is done to measure their gait parameters for usability in their walking aids. Favorable measuring parametric results were obtained and found satisfactory on comparing with standard walking system. The system is capable of determining the standard of care for the assessment and treatment of patients with balance, dizziness and mobility problems

Walking Foot Insoles for Dynamic Postural Analysis of Patients with Gait Imbalance: A Preliminary Report

780-783There are different cycles involved in the gait. In order to detect the pathological gait, it is necessary to understand the normal gait. During walk, various parameters were calculated to do analysis for providing further gait training. The aim of this study is to do the investigation and precise identification of deviation in gait pattern. Experimental study is done on thirty-one test subjects suffering from gait impairment. Further, data analysis on subjects is done to measure their gait parameters for usability in their walking aids. Favorable measuring parametric results were obtained and found satisfactory on comparing with standard walking system. The system is capable of determining the standard of care for the assessment and treatment of patients with balance, dizziness and mobility problems

Experimental Assessment of Cuff Pressures on the Walls of a Trachea-Like Model Using Force Sensing Resistors: Insights for Patient Management in Intensive Care Unit Settings

The COVID-19 outbreak has increased the incidence of tracheal lesions in patients who underwent invasive mechanical ventilation. We measured the pressure exerted by the cuff on the walls of a test bench mimicking the laryngotracheal tract. The test bench was designed to acquire the pressure exerted by endotracheal tube cuffs inflated inside an artificial model of a human trachea. The experimental protocol consisted of measuring pressure values before and after applying a maneuver on two types of endotracheal tubes placed in two mock-ups resembling two different sized tracheal tracts. Increasing pressure values were used to inflate the cuff and the pressures were recorded in two different body positions. The recorded pressure increased proportionally to the input pressure. Moreover, the pressure values measured when using the non-armored (NA) tube were usually higher than those recorded when using the armored (A) tube. A periodic check of the cuff pressure upon changing the body position and/or when performing maneuvers on the tube appears to be necessary to prevent a pressure increase on the tracheal wall. In addition, in our model, the cuff of the A tube gave a more stable output pressure on the tracheal wall than that of the NA tube

instrumented platform for assessment of isometric hand muscles contractions

Measurement of forces exerted by a human hand while performing common gestures is a highly valuable task for assessment of neurorehabilitation and neurological disorders, but also, for control of movement that could be directly transferred to assistive devices. Even though accurate and selective multi-joint measurement of hand forces is desirable in both clinical and research applications there is no commercially available device able to perform such measurements. Moreover, the custom-made systems used in research commonly impose limitations, such as availability of only single, predefined hand aperture. Furthermore, there is no consensus on design requirements for custom made measurement systems that would enable comparison of results obtained during research or clinical hand function studies. In an attempt to provide a possible solution for a device capable of multi-joint hand forces measurement and disseminate it to the research community, this paper presents the mechanical and electronic design of an instrumented platform for assessment of isometric hand muscles contractions. Some of the key features related to the developed system are: flexibility in placing the hand/fingers, fast and easy hand fitting, adjustability to different lengths, circumferences and postures of the digits, and the possibility to register individual bidirectional forces from the digits and the wrist. The accuracy of isometric force measurements was evaluated in a controlled test with the reference high accuracy force gauge device during which the developed system showed high linearity (R 2 = 0.9999). As the more realistic test, the device was evaluated when force was applied to individual sensors but also during the intramuscular electromyography (iEMG) study. The data gathered during the iEMG measurements was thoroughly assessed to obtain three appropriate metrics; the first estimating crosstalk between individual force sensors; the second evaluating agreement between measured forces and forces estimated through iEMG; and the third providing qualitative evaluation of hand force in respect to activations of individual muscle units. The results of these analyses performed on multiple joint forces show agreement with previously published results, but with the difference that in that case, the measurement was performed with a single degree of freedom device. (Less

Assessment of a Wearable Force- and Electromyography Device and Comparison of the Related Signals for Myocontrol

In the frame of assistive robotics, multi-finger prosthetic hand/wrists have recently appeared,offering an increasing level of dexterity; however, in practice their control is limited to a few handgrips and still unreliable, with the effect that pattern recognition has not yet appeared in the clinicalenvironment. According to the scientific community, one of the keys to improve the situation ismulti-modal sensing, i.e., using diverse sensor modalities to interpret the subject’s intent andimprove the reliability and safety of the control system in daily life activities. In this work, wefirst describe and test a novel wireless, wearable force- and electromyography device; throughan experiment conducted on ten intact subjects, we then compare the obtained signals bothqualitatively and quantitatively, highlighting their advantages and disadvantages. Our resultsindicate that force-myography yields signals which are more stable across time during whenevera pattern is held, than those obtained by electromyography. We speculate that fusion of the twomodalities might be advantageous to improve the reliability of myocontrol in the near future

Regressing Grasping Using Force Myography: An Exploratory Study

Background: Partial hand amputation forms more than 90% of all upper limb amputations. This amputation has a notable efect on the amputee’s life. To improve the quality of life for partial hand amputees diferent prosthesis options, including externallypowered prosthesis, have been investigated. The focus of this work is to explore force myography (FMG) as a technique for regressing grasping movement accompanied by wrist position variations. This study can lay the groundwork for a future investigation of FMG as a technique for controlling externally-powered prostheses continuously. Methods: Ten able-bodied participants performed three hand movements while their wrist was fxed in one of six predefned positions. The angle between Thumb and Index fnger (θTI), and Thumb and Middle fnger (θTM) were calculated as measures of grasping movements. Two approaches were examined for estimating each angle: (i) one regression model, trained on data from all wrist positions and hand movements; (ii) a classifer that identifed the wrist position followed by a separate regression model for each wrist position. The possibility of training the system using a limited number of wrist positions and testing it on all positions was also investigated. Results: The frst approach had a correlation of determination (R2) of 0.871 for θTI and R2 θTM = 0.941. Using the second approach R2 θTI = 0.874 and R2 θTM = 0.942 were obtained. The frst approach is over two times faster than the second approach while having similar performance; thus the frst approach was selected to investigate the efect of the wrist position variations. Training with 6 or 5 wrist positions yielded results which were not statistically signifcant. A statistically signifcant decrease in performance resulted when less than fve wrist positions were used for training. Conclusions: The results indicate the potential of FMG to regress grasping movement, accompanied by wrist position variations, with a regression model for each angle. Also, it is necessary to include more than one wrist position in the training phase

Improving the Robustness of Electromyogram-Pattern Recognition for Prosthetic Control by a Postprocessing Strategy

Electromyogram (EMG) contains rich information for motion decoding. As one of its major applications, EMG-pattern recognition (PR)-based control of prostheses has been proposed and investigated in the field of rehabilitation robotics for decades. These prostheses can offer a higher level of dexterity compared to the commercially available ones. However, limited progress has been made toward clinical application of EMG-PR-based prostheses, due to their unsatisfactory robustness against various interferences during daily use. These interferences may lead to misclassifications of motion intentions, which damage the control performance of EMG-PR-based prostheses. A number of studies have applied methods that undergo a postprocessing stage to determine the current motion outputs, based on previous outputs or other information, which have proved effective in reducing erroneous outputs. In this study, we proposed a postprocessing strategy that locks the outputs during the constant contraction to block out occasional misclassifications, upon detecting the motion onset using a threshold. The strategy was investigated using three different motion onset detectors, namely mean absolute value, Teager–Kaiser energy operator, or mechanomyogram (MMG). Our results indicate that the proposed strategy could suppress erroneous outputs, during rest and constant contractions in particular. In addition, with MMG as the motion onset detector, the strategy was found to produce the most significant improvement in the performance, reducing the total errors up to around 50% (from 22.9 to 11.5%) in comparison to the original classification output in the online test, and it is the most robust against threshold value changes. We speculate that motion onset detectors that are both smooth and responsive would further enhance the efficacy of the proposed postprocessing strategy, which would facilitate the clinical application of EMG-PR-based prosthetic control

Design of a low-cost sensor matrix for use in human-machine interactions on the basis of myographic information

Myographic sensor matrices in the field of human-machine interfaces are often poorly developed and not pushing the limits in terms of a high spatial resolution. Many studies use sensor matrices as a tool to access myographic data for intention prediction algorithms regardless of the human anatomy and used sensor principles. The necessity for more sophisticated sensor matrices in the field of myographic human-machine interfaces is essential, and the community already called out for new sensor solutions. This work follows the neuromechanics of the human and designs customized sensor principles to acquire the occurring phenomena. Three low-cost sensor modalities Electromyography, Mechanomyography, and Force Myography) were developed in a miniaturized size and tested in a pre-evaluation study. All three sensors comprise the characteristic myographic information of its modality. Based on the pre-evaluated sensors, a sensor matrix with 32 exchangeable and high-density sensor modules was designed. The sensor matrix can be applied around the human limbs and takes the human anatomy into account. A data transmission protocol was customized for interfacing the sensor matrix to the periphery with reduced wiring. The designed sensor matrix offers high-density and multimodal myographic information for the field of human-machine interfaces. Especially the fields of prosthetics and telepresence can benefit from the higher spatial resolution of the sensor matrix