Human Control Law and Brain Activity of Voluntary Motion by Utilizing a Balancing Task with an Inverted Pendulum

Abstract

Human characteristics concerning voluntary motion control are investigated, because this motion is fundamental for the machine operation and human-computer system. Using a force feedback haptic device and a balancing task of a virtual inverted pendulum, participants were trained in the task, and hand motion/force was measured, and brain activity was monitored. First, through brain analysis by near-infrared spectroscopy (NIRS) and motion analysis of the pendulum, we identified a participant who was the most expert. Next, control characteristics of the most expert were investigated by considering the operational force and delay factor of a human. As a result, it was found that predictive control based on velocity information was used predominantly although a perception feedback control against the pendulum posture worked. And it was shown that an on-off intermittency control, which was a strategy for the skilled balancing, can be described well by a liner model involving two types of time shifts for the position and velocity. In addition, it was confirmed that the cortex activity for observation in an ocular motor control area and visual processing area was strong to enhance above-mentioned control strategies.

Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses

“…Additionally, a multivariate approach was applied to explore the discernibility of the two tasks based on their spatial brain activation patterns only. Comfort ratings were obtained throughout the experiment as other studies have reported that participants may withdraw from fNIRS recordings due to headset discomfort (Suzuki et al, 2010;Cui et al, 2011;Rezazadeh Sereshkeh et al, 2018). In addition, we evaluated whether the presence of specific physical features of participants (e.g., hair thickness, root density, or color) affected fNIRSsignal quality and subsequent decoding results (Koizumi et al, 1999;Coyle et al, 2005;Cui et al, 2011;Khan et al, 2012;Fang et al, 2018).…”

Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: Effects on signal quality and sensitivity

“…This decision ensured that the optode setup would maximally consist of 24 optodes (3 optodes per layout × 4 approaches × 2 motor-imagery tasks), which should constitute a reasonably comfortable setup for participants and thus should prevent them from withdrawing from fNIRS recordings due to setup-related discomfort [48][49][50] . This selection was carried out at the individual subject level.…”

Comparison of Pixel-based Position Input and Direct Acceleration Input for Virtual Stick Balancing Tests

“…The nature and the characteristics of this feedback process is still a subject of debates. Investigation of different human balancing tasks, such as simple quiet standing [1][2][3][4][5] standing on pinned or rolling balance boards [6,7], stick balancing on the fingertip or on a Ping-Pong racket [8][9][10][11], may help in identifying and in understanding the underlying control mechanism. Experimental investigation of these balancing tasks requires motion capture system, e.g., IMU sensors fixed on the balanced object or a camera system, which records the spatial position of markers fixed on the balanced object.…”