IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, VOL. 7, NO. 1, MARCH 1999 1 Guidance-Based Quantification of Arm Impairment Following Brain Injury: A Pilot Study David J. Reinkensmeyer, Member, IEEE, Julius P. A. Dewald, and William Zev Rymer, Member, IEEE Abstract—This paper reports the design and preliminary test- ing of a device for evaluating arm impairment after brain injury. The assisted rehabilitation and measurement (ARM) Guide is capable of mechanically guiding reaching and retrieval move- ments across the workspace and of measuring constraint forces and range of motion during guidance. We tested the device on four hemiplegic brain-injured individuals and four unimpaired control subjects. During guided movement, the brain-injured subjects generated distinct spatial patterns of constraint force with their impaired arms that were consistent with the stan- dard flexion and extension “synergies” described in the clinical literature. In addition, the impaired arms exhibited well-defined workspace deficits as measured by the ARM Guide. These results suggest that constraint force and range of motion measurements during mechanically guided movement may prove useful for precise monitoring of arm impairment and of the effects of treat- ment techniques targeted at abnormal synergies and workspace deficits. Index Terms—Biological motor systems, biomechanics, motion measurement, nervous system, robots. I. INTRODUCTION A PPROXIMATELY 400000 individuals survive a stroke in the United States each year [1]. Of these, over 50% incur chronic motor disability [2]. Tens of thousands more people annually experience traumatic brain injuries that cause motor deficits [3]. Currently, little mechanical sensing and actuation technology is used in the clinical evaluation of motor impairments after such brain insult. Imaging technology is used to localize central nervous system (CNS) lesions, and electrophysiological technology, such as electromyogram (EMG) and H-reflex testing, is sometimes used to quantify muscle and reflex activation. However, evaluation of the biomechanical effects of neural damage relies to a large degree on visual and haptic observations by therapists and Manuscript received October 1, 1997; revised May 7, 1998. This work was supported by NIH-F32HD08067, NIDRR-H133P20016, and the Ralph and Marian C. Falk Medical Research Trust. D. J. Reinkensmeyer was with the Department of Physical Medicine and Rehabilitation, Northwestern University Medical School, and the Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611 USA. He is now with the Department of Mechanical and Aerospace Engineering, University of California at Irvine, Irvine, CA 92697 USA. J. P. A. Dewald is with the Department of Physical Medicine and Reha- bilitation, Northwestern University Medical School, the Programs in Physical Therapy, Northwestern University, and the Sensory Motor Performance Pro- gram, Rehabilitation Institute of Chicago, Chicago, IL 60611 USA. W. Z. Rymer is with the Department of Physiology, Northwestern Univer- sity, the Department of Physical Medicine and Rehabilitation, Northwestern University Medical School, and the Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611 USA. Publisher Item Identifier S 1063-6528(99)01170-2. physicians. Appropriately designed machines could enhance subjective, haptic evaluation. In particular, machine-assisted evaluation might improve the objectivity, sensitivity, and diagnostic power of the hands-on, clinical exam [4]–[7]. By “appropriately designed” machines we mean machines targeted at the distinctive motor impairments that arise after brain injury. These impairments include weakness [8], [9], contracture [10], spasticity [11], and incoordination [12], [13]. Several mechanical devices have been developed for quan- tifying weakness, contracture, and spasticity, some of which are routinely used in clinics. For example, dynamo meters are available for measuring weakness [14] and goniometers for measuring contracture [15]. Devices for measuring spasticity at the elbow, ankle, and other joints are also under development [16], [17] but have not yet found widespread use. A shortcoming of current quantification devices is that they typically focus on single-joint movement while motor deficits after brain injury often involve impaired multijoint coordination. In particular, arm and leg movement after brain injury often appears to be limited by relatively tight, stereo- typical coupling of motion at adjacent joints, induced by abnormal coactivation of muscles acting at the adjacent joints [18]–[20]. This coupling is clinically referred to as an “abnor- mal synergy.” Abnormal synergies were described in detail by Brunnstrom [21] and are typically grouped into flexion and extension synergies for the arm and leg (Table I). A key functional consequence of abnormal synergies is thought to be a decreased capacity to move the affected limb to desired locations in space [21]. Currently, few quantitative methods are available to char- acterize abnormal synergies and their effects on a limb’s workspace. In rehabilitation practice abnormal synergies are typically evaluated qualitatively based on the descriptive stud- ies by Brunnstrom. Quantitative scoring in the clinic is some- times achieved using the Fugl–Meyer motor performance exam [22], which is a cumulative score that coarsely grades a patient’s ability to move joints independently or in various patterns based on Brunnstrom’s descriptions (see Table I). As for technology-based measurement, multiple-muscle EMG’s combined with multiaxial force sensing have been used to characterize abnormal muscle synergies [23], but the com- plexity of these procedures would appear to hinder their routine clinical use. Isometric, multiaxis force target matching is another technique which in preliminary studies has shown promise for quantifying the multijoint effects of abnormal synergies on directional weakness [24]. However, important unanswered questions remain concerning how to quantify 1063–6528/99$10.00  1999 IEEE