P147. Infrared-based kinematic read-out of TMS-elicited complex finger movements: A pilot study

Abstract

Introduction Navigated transcranial magnetic stimulation (nTMS) is a commonly used tool to study the human motor system and central motor control. In this context, usually an electromyogram (EMG) over a predefined muscle is used to obtain motor evoked potential (MEP) amplitudes for post hoc analysis. Yet, conclusive evidence exists that the same cortical site renders outgoing impulses to different muscles (divergence, synergies) despite focal stimulation. Similarly, a single navigated target controlled TMS pulse generates movement not in one but in multiple muscles. In this context, novel kinematic read-out methods might be a promising means for more precise read-out of central motor control mechanisms, e.g. in terms of movement characterization. We hypothesized that 3D kinematic detection should be more suitable than EMG as a read-out method in TMS studies of simple finger movements. To this end, we study the utilization of LeapMotion, a novel infrared movement sensor, and compare it with classic EMG traces in terms of its accuracy in detecting simple finger movements induced by TMS. Methods Subjects were trained to imagine a specific movement following visual presentation of the particular letter (TARGET) assigned to a particular finger of the dominant hand. NTMS was utilized to always stimulate (120% resting motor threshold) a subject’s ( n = 5) first dorsal interosseus (FDI) hot-spot directly after any TARGET presentation. Every TARGET was presented 20 times. Elicited movements were recorded simultaneously by LeapMotion, an infrared movement sensor placed below the hand, and EMG over four muscles (FDI, adductor digit minimi, abductor policis brevis and extensor digitorum communis). Motor-evoked potential amplitudes (MEP) and movement kinematics (LeapMotion) were used to calculate TARGET prediction rates. In order to compare EMG- and LeapMotion based estimators, we analyzed quality parameters (mean, median, deviation, sensitivity and specificity). Results When comparing read-outs following stimulation of the FDI-hot-spot, LeapMotion data allowed for significantly ( p Conclusion These results show that kinematic features of movements obtained by LeapMotion are important information not detectable by means of EMG. A possible explanation would be that LeapMotion is more flexible of a tool when it comes to multiple degrees of freedom. Imagery proofed to be valuable to achieve motor cortex output control in previous studies consistent with our data.