2014 · 66 citations · 17 references
EngineeringBiomedical EngineeringRehabilitation MedicineAssistive TechnologyRoboticsSensorsForce SensingForce SensorsMechanical SensorsRehabilitation BiomechanicsRehabilitation RoboticsTactile SensingBiomedical Force SensingElectromyographyElectromyography Signal AcquisitionForce Estimation From ElectromyographySurface ElectromyographyWearable Force SensingWearable Force SensorsWrist Force Sensors
In rehabilitation robotics it is highly desirable to find novel human-machine interfaces for the disabled, in particular to substitute or augment surface electromyography (sEMG), trying to keep at the same time its easiness of use, precision and non-invasiveness. In this paper we design and demonstrate one such device, based upon Force-Sensing Resistors (FSRs). An array of 10 FSRs was wrapped around the proximal section of the forearm of ten intact subjects engaged in pressing on an accurate force sensor with their fingers (this includes the rotation of the thumb). The FSRs would detect the forearm surface deformations induced by muscle activity; the signals provided by the FSRs were then matched to the recorded forces. The experimental results show that finger forces can be predicted using this device with the same accuracy obtained in literature using sEMG. The device, even as an academic prototype, weighs about 65 grams and costs around 50 EUR. Thus, it is remarkably light and cheap in comparison to standard sEMG electrode arrays.
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A training algorithm for optimal margin classifiers
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