Hot spot hound: A novel robot-assisted platform for enhancing TMS performance

Abstract

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique that produces excitatory depolarization in the neurons located in the cerebral cortex. In order to proficiently stimulate a specific cerebral area it is of main importance the correct positioning and maintaining of the magnetic coil, while avoiding the mismatch due to subject head-coil relative movement. Hot Spot Hound is a novel robot-assisted experimental platform for enhancing TMS stimulation performance. It integrates a commercial optoelectronic neuronavigation system (E.M.S. srl, Italy) for gathering data on the relative pose (position and orientation) of subject's scalp and TMS coil, and a service robotic arm designed for human interaction (LWR system by KUKA, Germany). Besides integrating and synchronizing different platform sub-systems, we implement a control strategy to center the stimulation point and compensate for involuntary subject movements. Specifically, the proposed control maintains constant over time the homogeneous transformation matrix between the pose of the coil and of the head. The value of position stiffness has been chosen in order to assure the better compromise between coil position and orientation error, and the safety of the experimental subject. In this paper we show that Hot Spot Hound can provide coil position and orientation errors well beyond the ones achieved by manual experimenter, while assuring safety in the physical interaction with the stimulated subject.

Characterizing an electronic–robotic targeting platform for precise and fast brain stimulation with multi-locus transcranial magnetic stimulation

“…These increases may be caused by the robot weight applied in the wood stand that can press the coil set slightly closer to the TMS calibrator; even a small variation will cause an observable increase in the maximum resulting E-fields. Our findings indicate that the robotized–electronic system achieves superior accuracy compared to manual positioning and demonstrates comparable stability and accuracy to existing robotized TMS systems (Richter et al ., 2010; Pennimpede et al ., 2013; Grab et al ., 2018; Goetz et al ., 2019; Noccaro et al ., 2021). Our open-source platform for robotic–electronic targeting can be used to automate TMS protocols, including stimulation target, hotspot identification, and precise motor mapping, employing closed-loop algorithms while minimizing reliance on user experience and subjective analysis (Harquel et al ., 2017; Tervo et al ., 2020; Weise et al ., 2023).…”

Achieving Dexterous Bidirectional Interaction in Uncertain Conditions for Medical Robotics

“…Other applications of co-bots in robotics involved automated diagnostics (e.g., ultrasound scan) and robot-aided TMS (Transcranial Magnetic Stimulation) [15], [16]. The automation of diagnostic technology looks into the possibility of completely automating examinations such as the ultrasound scan, looking into machine learning and neural network to identify anomalies in the image and perform a diagnosis.…”

Evaluation of Hand-Eye and Robot-World Calibration Algorithms for TMS Application

“…To overcome the drawbacks due to manually performing the procedure, e.g. low accuracy and low repeatability in coil positioning and support, robot-aided TMS systems have been proposed by a number of studies [3], [4], [5], [6], [7]. Those systems employ a robotic manipulator to move the coil on the stimulation target with high accuracy and repeatability.…”