title: The influence of motor system degradation on the control of handwriting movements: a dynamical systems analysis.
abstract: The complex dynamics of the human hand/arm system need to be precisely controlled to produce fine movements such as those found in handwriting. This study employs dynamical systems analysis techniques to further understand how this system is controlled when it is functioning well and when it is compromised through motor function degradation (e.g. from tremor). Seven people with and 16 people without multiple sclerosis (MS) participated in this study. Tremor was assessed using spirography with participants being separated into "tremor" (6 people with and 1 person without MS; 2 male, 5 female; age range 40-68) and control (1 person with and 15 people without MS; 5 male, 11 female, age range 18-59) groups. Participants wrote the pseudo-word "lanordam" six times on a digitizer, in a quiet as well as a noisy, mildly stressful environment. Velocity profiles of the pen tip for the best four trials were concatenated and analyzed to determine their dimensionality (a measure of the number of control variables) and Lyapunov exponents (a measure of predictability). Results indicate that the velocity profiles for people with tremor were lower dimensional and had less predictable dynamics than for controls, with no effect of sound condition. Interpreted in the context of related research, it was speculated that the lower dimensionality reflected the loss of control of variables related to the minimization of movement variability, resulting in less predictable movements.
authors.affiliation: Motor Control Laboratory, Arizona State University, Tempe, AZ 85287-0404, USA. mitchell.longstaff@asu.edu
authors.forename: M G
authors.initials: MG
authors.lastname: Longstaff
authors.forename: R A
authors.initials: RA
authors.lastname: Heath
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D001143:Arousal / Q000502:physiology; D001288:Attention / Q000502:physiology; D001696:Biomechanical Phenomena; D003196:Computer Graphics; D005260:Female; D006236:Handwriting; D006801:Humans; D007596:Joints / Q000502:physiology; D008297:Male; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000175:diagnosis / Q000503:physiopathology*; D016571:Neural Networks, Computer; D009469:Neuromuscular Junction / Q000503:physiopathology; D017711:Nonlinear Dynamics; D011597:Psychomotor Performance / Q000502:physiology*; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted; D013597:Systems Analysis; D014202:Tremor / Q000175:diagnosis / Q000503:physiopathology*