ARTICLES Quantifying Motion in Dystonic Syndromes: The Bare Essentials Anne Beuter, Alexandre Legros, Laura Cif, and Philippe Coubes Abstract: Quantifying movement disorders is becoming crucially important in neurosurgery units to evaluate the efficacy of new therapeutic interventions such as deep brain stimulation. Kinematic analysis, available for more than a century, may represent an adequate solution to this problem. However, quantifying movement disorders poses a number of technical problems. To help clinicians quantify movement disorders, the authors present data recorded in patients with dystonic syndromes and explore the question of move- ment “normality” in these patients when they receive deep brain stimulation of the internal globus pallidus. In particular, they show that when one control group (n = 11) and a group of dystonic patients (n = 11) are compared, it is possible to detect subtle changes in the performance of a double-handed finger to nose test. These differences persist in the absence of differences in the clinical evaluation of these patients. Suggestions regarding the compromises to make and pitfalls to avoid when quantifying movement disorders are discussed. Key Words: Dystonia, Deep brain stimulation, Clinical rating scales, Motion analysis. (J Clin Neurophysiol 2004;21: 209 –214) Chronic impairment is a common consequence of neurologic disorders. Therefore, precise measurement of health-related outcomes such as disability, handicap, and quality of life is crucial to evaluate the efficacy of therapeutic interventions (Hobart et al., 1996). Although several clinical rating scales are available and used to evaluate patients with movement disorders, these tests are designed to detect clinical changes under specific circumstances. They are not adapted to detect subclinical changes, nor are they designed to examine sepa- rately the various components of voluntary movements (such as the ballistic or ramp components). Therefore, there is a need to quantify movement disorders. A number of articles on this topic have been published (see for example Ingvars- son et al., 1999; O’Suilleabhain and Dewey, 2001). Quantifying movement disorders presents several dif- ficulties. A first difficulty is that the human movement rep- ertoire is rich, and although we know what a “normal” movement looks like, there is no accepted operational defi- nition of what a normal movement should be. A second difficulty is related to the nature of movement disorders that are extremely varied in their manifestations. They may fluc- tuate, appear intermittently, be nonspecific, or even at times be very subtle. Therefore, there does not exist one single solution to quantify movement disorders. A third difficulty deals with the fact that all evaluation methods (be they qualitative or quantitative) have inherent limitations. Limita- tions of clinical rating scales such as lack of reliability or drift are well known, but one should keep in mind that quantifi- cation of movement also has limitations such as noise, cali- bration problems, and artifacts (Elble and Koller, 1990; Hobart et al., 1996). Moreover, the methods used must be comprehensively evaluated, not only in terms of clinical usefulness, but also with regard to their scientific soundness (i.e., validity, reliability) (Hobart et al., 1996) Yet quantification of movement disorders with valid, reliable, and sensitive tools could bring a more detailed understanding of motor control processes. Much could be gained by exploring how motor functions can be restored in patients who have lost these motor functions and who are receiving deep brain stimulation (DBS) or functional electri- cal stimulation. Such questions could include the detection at a very early stage on the effect of DBS on motor control, the monitoring of the long term effect of DBS on selected motor components of voluntary movement and muscle tone, and the exchange of information between an assistive artificial im- planted system interfaced with the human body. In this article, we suggest a way to quantify dystonic syndromes and present data recorded in a group of patients and a control group. Through this example, we illustrate the choices that must be made (i.e., instruments to use, tests to investigate and analyses to perform) to quantify a movement disorder in an appropriate way. Movement Disorder Research Unit, Ho `pital Gui de Chauliac, Universite ´ de Montpellier I, Montpellier, France Address correspondence and reprint requests to Dr. Anne Beuter, Efficience et De ´ficience Motrice (EA 2991), Institut de Biologie, Laboratoire de Physiologie, Universite ´ de Montpellier I, 34060 Montpellier Cedex, France; e-mail: anne.beuter@wanadoo.fr. Copyright © 2004 by Lippincott Williams & Wilkins ISSN: 0736-0258/04/2103-0209 Journal of Clinical Neurophysiology • Volume 21, Number 3, June 2004 209