Project title

Providing amputees with a functional artificial limb has been an area of active research for many years. Today, the most widely used prostheses are controlled by myoelectric systems using signals from surface electromyography (sEMG). However, these devices only allow one movement at a time and they are limited to a few degrees-of-freedom (DoF). This study examines the extent to which intramuscular electromyographic recordings (i.e signals recorded from inside a muscle or iEMG) can be used to effect direct proportional control of prostheses. These invasive recordings are less affected by signal cross-talk and may provide sources for multiple, independent channels of control. They may also enable more intuitive control effectively manage and control the large number of DoF that are possible in advanced prosthetic limbs. The main aim of this study is to examine what features of intramuscular recordings may be used in proportional control of prostheses. We will research on how different muscles coordinate during complex tasks that involve many muscles and the advantage of using multichannel recordings with respect to single channel. This study will propose features of intramuscular recordings that correlate with grasping force and that can be used for force estimation, thereby for proportional control. The project is expected to provide techniques to develop a system with high social impact, as the control will be more intuitive and allow improved daily living activities for the users. The project is expected to have an impact on the scientific community, as it will open up for a multidisciplinary research area on invasive control of advanced prostheses.

The work in this project proposes a solution to address the current drawbacks of prostheses controlled by non-invasive muscle signals by providing novel means for extracting information from intramuscular EMG signals. We aim at providing amputees with a more intuitive and simultaneous control of up to 5 DoFs prosthesis.

Kamavuako EN , Rosenvang JC, Bøg MF, Smidstrup A, Erkocevic E, Niemeier MJ, Jensen W, Farina D. Influence of the feature space on the estimation of hand grasping force from intramuscular EMG. Biomedical Signal Processing and Control. 2012 in press.

Kamavuako EN Englehart K, Jensen W, Farina D. Simultaneous and proportional force estimation in multiple degrees of freedom from intramuscular EMG. IEEE Trans Biomed Eng. 2012 in press.

Kamavuako EN and Rosenvang JC. Hysteresis in the EMG-force relationship: Towards an optimal model for the estimation of force. Muscle Nerve 2012 in press.

Kamavuako EN, Farina D, Yoshida K, Jensen W. Estimation of grasping force from features of intramuscular EMG signals with mirrored bilateral training. Ann Biomed Eng. Vol. 40, No. 3, 2012, p. 648-656

Kamavuako EN, Farina D, Jensen W. Use of sample entropy extracted from intramuscular EMG signals for the estimation of force. International Federation for Medical and Biological Engineering Proceedings, Vol. 34, 2011, s. 125-128.

Bøg MF, Erkocevic E, Niemeier MJ, Rosenvang JC, Smidstrup A, Kamavuako EN. Investigation of the linear relationship between grasping force and features of intramuscular EMG. International Federation for Medical and Biological Engineering Proceedings, Vol. 34, 2011, s. 121-124.

Smidstrup A, Erkocevic E, Niemeier MJ, Bøg MF, Rosenvang JC, Kamavuako EN. A comparison study of EMG features for force prediction. Symposium Proceedings of the International Conference on Advanced Limb Prosthetics, MEC '11, 14-19 August 2011, Fredericton, Canada, p. 93-96.

Rosenvang JC, Niemeier MJ, Erkocevic E, Bøg MF, Smidstrup A, Kamavuako EN. Towards an optimal model for the estimation of force from intramuscular EMG. Symposium Proceedings of the International Conference on Advanced Limb Prosthetics, MEC '11, 14-19 August 2011, Fredericton, Canada, p. 97-100.