Improving Optical Myography via Convolutional Neural Networks

  title={Improving Optical Myography via Convolutional Neural Networks},
  author={Christian Nissler and Imran Badshah and Claudio Castellini and Wadim Kehl and Nassir Navab},
In order to improve the accuracy and reliability of myocontrol (control of prosthetic devices using signals gathered from the human body), novel kinds of sensors able to detect muscular activity are being explored. In particular, Optical Myography (OMG) consists of optically tracking and decoding the deformations happening at the surface of the body whenever muscles are activated. OMG potentially requires no devices to be worn, but since it is an advanced problem of computer vision, it incurs a… 
3 Citations
Evaluation of Optical Myography Sensor as Predictor of Hand Postures
The sensor is evaluated upon the construction of a feasible and low-cost sensor that monitors both the front and the back of the forearm and its performance as a predictor of eight static postures, including the thumb and the fingers motion proved to be comparable to more mature techniques.
Optical myography system for hand posture and gesture recognition
In this work, an optical myography system is demonstrated as a promising alternative to monitor hand posture and gestures of the user. This technique is based on accompanying muscular activities
Reconstruction and Scalable Detection and Tracking of 3D Objects
This work explores methods to create richlytextured and geometrically accurate models of real-life objects and investigates on how to improve in the domain of 3D object detection and pose estimation, focusing especially on scalability.


Optical Myography: Detecting Finger Movements by Looking at the Forearm
If further successfully tested in the large, this approach could lead to vision-based intent detection of amputees, with the main application of letting such disabled persons dexterously and reliably interact in an augmented-/virtual-reality setup.
OMG: Introducing optical myography as a new human machine interface for hand amputees
Given the recent progress in the development of computer vision, it is nowadays possible to optically track features of the human body with unprecedented precision. We take this as a starting point
High-density force myography: A possible alternative for upper-limb prosthetic control.
This work investigates the suitability of using high-density force myography (HD-FMG) for prosthetic control and finds that with informed, symmetric channel reduction, classification error could be decreased to 0.02%.
Novel Method for Predicting Dexterous Individual Finger Movements by Imaging Muscle Activity Using a Wearable Ultrasonic System
This work presents a novel ultrasound imaging based control strategy for upper arm prosthetics that can overcome many of the limitations of myoelectric control.
Force Myography to Control Robotic Upper Extremity Prostheses: A Feasibility Study
It is shown that it is possible to classify six primary grips important in activities of daily living using FMG with an accuracy of above 70% in the residual limb, and strategies to increase classification accuracy, such as using the available modes on the Bebionic3, allowed results to improve.
Transradial Amputee Gesture Classification Using an Optimal Number of sEMG Sensors: An Approach Using ICA Clustering
The proposed method is a model-based approach where a combination of source separation and Icasso clustering was utilized to improve the classification performance of independent finger movements for transradial amputee subjects.
Myoelectric forearm prostheses: state of the art from a user-centered perspective.
Focus should be on validating EMG-sensing results with patients, improving simultaneous control of wrist movements and grasps, deriving optimal parameters for force and position feedback, and taking into account the psychophysical aspects of feedback, such as intensity perception and spatial acuity.
Control of Hand Prostheses Using Peripheral Information
This review presents and discusses the recent results achieved by using electromyographic signals, recorded either with surface (sEMG) or intramuscular (i EMG) electrodes, and electroneurographic (ENG) signals.
AprilTag: A robust and flexible visual fiducial system
  • E. Olson
  • Computer Science
    2011 IEEE International Conference on Robotics and Automation
  • 2011
This work describes a new visual fiducial system that uses a 2D bar code style “tag”, allowing full 6 DOF localization of features from a single image, incorporating a fast and robust line detection system, a stronger digital coding system, and greater robustness to occlusion, warping, and lens distortion.
Advances in surface EMG: recent progress in clinical research applications.
state of the art applications of surface EMG techniques to a) the external anal sphincter in relation to episiotomy and incontinence; b) the assessment of postural control mechanisms; c) exercise physiology, electrical stimulation and muscle cramps; and d) ergonomics and work-related neuromuscular disorders.