Training finger individuation with a mechatronic-virtual reality system leads to improved fine motor control post-stroke
© Thielbar et al.; licensee BioMed Central. 2014
Received: 3 July 2014
Accepted: 5 December 2014
Published: 26 December 2014
Dexterous manipulation of the hand, one of the features of human motor control, is often compromised after stroke, to the detriment of basic functions. Despite the importance of independent movement of the digits to activities of daily living, relatively few studies have assessed the impact of specifically targeting individuated movements of the digits on hand rehabilitation. The purpose of this study was to investigate the impact of such finger individuation training, by means of a novel mechatronic-virtual reality system, on fine motor control after stroke.
An actuated virtual keypad (AVK) system was developed in which the impaired hand controls a virtual hand playing a set of keys. Creation of individuated digit movements is assisted by a pneumatically actuated glove, the PneuGlove. A study examining efficacy of the AVK system was subsequently performed. Participants had chronic, moderate hand impairment resulting from a single stroke incurred at least 6 months prior. Each subject underwent 18 hour-long sessions of extensive therapy (3x per week for 6 weeks) targeted at finger individuation. Subjects were randomly divided into two groups: the first group (Keypad: N = 7) utilized the AVK system while the other group (OT: N = 7) received a similarly intensive dose of occupational therapy; both groups worked directly with a licensed occupational therapist. Outcome measures such as the Jebsen-Taylor Hand Function Test (JTHFT), Action research Arm Test (ARAT), Fugl-Meyer Upper Extremity Motor Assessment/Hand subcomponent (FMUE/FMH), grip and pinch strengths were collected at baseline, post-treatment and one-month post-treatment.
While both groups exhibited some signs of change after the training sessions, only the Keypad group displayed statistically significant improvement both for measures of impairment (FMH: p = 0.048) and measures of task performance (JTHFT: p = 0.021). Additionally, the finger individuation index – a measure of finger independence – improved only for the Keypad group after training (p = 0.05) in the subset (Keypad: N = 4; OT: N = 5) of these participants for which it was measured.
Actively assisted individuation therapy comprised of non task-specific modalities, such as can be achieved with virtual platforms like the AVK described here, may prove to be valuable clinical tools for increasing the effectiveness and efficiency of therapy following stroke.
KeywordsStroke Hand Fingers Individuation Occupational therapy Rehabilitation
Dexterous manipulation of the digits is one of the hallmarks of human motor control. While biomechanical and neurological constraints do limit independent movement of the fingers and thumb to some extent[1, 2], the capabilities of the hand are quite remarkable, far surpassing state-of-the-art robotic hands, for example. Considerable neurological resources are devoted to support hand manipulation, as evidenced by the large representation in both primary motor and sensory cortices. Specialized, phylogenetically recent corticomotoneuronal pathways seem to be necessary for the creation of independent finger movements. These pathways continue to develop postnatally, and do not form synapses with their motoneuronal targets until months after birth. Unfortunately, these pathways may be damaged by neurological incidents, such as stroke. Indeed, individuation can be compromised even when the stroke produces only small, or lacunar lesions. The diminished individuation impacts a variety of activities from typing to grasp and transport of objects.
Despite the functional importance of hand motor control, relatively few studies have examined the effects of training individuated digit movements post-stroke. Taheri et al., investigated the use of the FINGER robot to train individuation for the middle and ring fingers. Sale et al., examined the feasibility of using a hand-specific robot, the Amadeo® System, in the early phases of stroke rehabilitation. Merians et al., created a set of virtual reality scenarios, including a virtual piano, in order to train the upper extremity after stroke. They observed improvements in a metric they created to assess finger independence. The efficacy of this type of training in comparison to more standard occupational therapy methods, however, is not clear.
We developed an actuated virtual keypad (AVK) system specifically targeting independence of finger movements. Virtual reality was employed as it permits quick, facile alterations in task challenge (e.g., the amount of digit flexion required to play a key) as well as the ability to map different notes to a given key, thereby providing for a limitless set of sounds to be played with a finite set of keys. In this study, we sought to determine whether training with this system would improve independent finger movements and facilitate general task performance in stroke survivors with chronic hemiparesis. We sought to compare the effectiveness of this novel intervention with the outcomes from performing occupational therapy focused on the hand.
While one group trained with a therapist on the AVK, another group received a similar time-dose of intensive occupational therapy focused on fine motor control and finger individuation. We hypothesized that training with the AVK would translate into improved generalized hand motor control to the same extent or beyond that exhibited by the group receiving intensive occupational therapy focusing on the hand. Equivalent success would suggest that the AVK therapy could be employed with multiple users guided by a single therapist or even in remote therapy opportunities to create greater efficiency in the provision of therapy services to this population.
Actuated virtual keypad
A total of 16 subjects enrolled in the study. Participants had chronic hemiparesis resulting from a single hospitalized ischemic or hemorrhagic stroke occurring at least 6 months prior to enrolling in the study. Additionally, the participants exhibited mild to moderate hand impairment as evidenced by a score of 5 or 6 on the Stage of Hand subsection of the Chedoke-McMaster Stroke Assessment scale (CMSA-H). Each participant demonstrated limitations with fine motor control and finger individuation, but was able to perform at least two of the following three movements: 1) abduction of the digits to full range of motion; 2) touching of the tip of the thumb to the tip of the little finger; 3) smooth reversal between full flexion and full extension of the digits. Potential subjects were excluded if they: 1) were receiving outpatient physical or occupational therapy; 2) had biomechanical limitations (e.g., contracture) which limited passive digit extension to 20° of finger flexion; 3) had received a botulinum toxin (e.g., Botox®) injection less than 6 months prior to enrollment, 4) had cognitive deficits limiting simple one-step commands, or 5) had significant upper extremity pain (rated as greater than 6/10). Northwestern University’s Institutional Review Board (Chicago, IL) approved the study design and participants signed written informed consent before enrolling in the study.
Participants were randomized into one of two treatment groups by drawing lots. Each participant in both groups worked individually with a research occupational therapist for a total of 18 one-hour training sessions 3 times per week for 6 weeks.
Assessment of the participant’s motor control was performed at three time points during the study: 1) prior to initiation of the training; 2) following the conclusion of the 18 training sessions; 3) one month after completion of all of the training sessions. A research therapist, blinded as to the participant’s group assignment, administered a battery of evaluations. The clinical outcome measures consisted of the Action Research Arm Test (ARAT), the Jebsen-Taylor Hand Function Test (JTHFT)[20, 21], the Upper Extremity Portion of the Fugl-Meyer Motor Assessment (FMUE) and the Hand subcomponent (FMH). Additionally, the following measurements of strength were also performed: grip strength (GS) (JAMAR 5030 J1 Hand Dynamometer), lateral pinch strength (LPS) (PG-60, B&L Engineering), and 3-point pinch strength (PPS) (PG-60, B&L Engineering).
Finally, we were able to obtain measurement of kinematic individuation for a subset of the participants in each group. The CyberGlove (CyberGlove Systems, LLC, San Jose, CA) was used to measure flexion/extension angles at each digit joint simultaneously. Initial position was a neutral posture for the forearm (0 degrees supination or pronation) and the digits. Participants were asked to move each digit independently throughout their range of motion, beginning from a neutral posture and proceeding through a fully extended posture to a comfortably flexed posture and back to neutral. Subjects were instructed to move at a comfortable speed (up to 10 sec per finger per trial) to minimize movement in the alternate digits. Wrist movement was prevented through splinting (FUTURO™, 3M) which was worn under the CyberGlove. Five successful trials were recorded per digit (25 total).
Total scores for each assessment period for each participant were used for the ARAT, FMUE, and CH. The mean score for the three trials taken during each assessment session were averaged to obtain the measures for maximum GS, LPS, and PPS. In accordance with other studies, we did not include the handwriting portion of the JTHFT in our outcome measure. Scoring for this item is dependent upon which hand is dominant and which hand is impaired. In this study we do not differentiate hand dominance and side of impairment in analysis; therefore it was not appropriate to include this item in analysis. The total completion time across the other 6 tasks was used.
Statistical analyses were performed separately for each group to determine whether the training impacted the outcome measures. Non-parametric Friedman Test for repeated measures was employed due to the ordinal nature of much of the data and the relatively small sample sizes. If the main effect of evaluation session were found to be significant, post-hoc Wilcoxon signed-ranks tests were subsequently performed to determine significant differences between the three different evaluations (pre-treatment, post-treatment, and one-month follow-up). For the individuation indices, paired t-tests were utilized to compare the metrics across all digits from pre- to post-treatment.
To ascertain the effectiveness of the AVK treatment compared to the intensive hand therapy, noninferiority testing was performed as our between-group analysis. The inferiority margin, δ, was set according to the published minimally important clinical difference (MICD) in current literature when available (ARAT, FMUE, GS) and conservatively estimated for LPS and PPS based on reported minimal detectible changes (MDC). As the JTHFT has neither the MICD nor the MDC established, δ was estimated according to a 20% improvement from mean baseline scores. In cases for which the AVK treatment showed superiority to the OT treatment, post hoc t-tests were performed. To compare the baseline values for the outcomes between the groups, the Kruskal Wallis Test (KW) was used.
Months Post Stroke
42.9% left affected
71.4% left affected
Values of outcome measures and within-group analyses
In contrast, the Keypad group completed almost 1000 key presses each session (range 750–1200), with the majority of key presses occurring during the Song mode. Subjects in this group showed significant improvement on multiple measures between baseline and the one-month follow-up (Table 2). Improvements were observed both on measures of impairment and measures of performance. The FMH score improved by 1.9 (1.5) or 12% (p = 0.026). The JTHFT showed an average decrease of 33 seconds for the time to complete the 6 tasks (p = 0.028). The ARAT also showed improvement, with a score increase of 4.8 (7.2). Improvement in digit individuation was also apparent in the subset of Keypad group members who performed these tests (Figure 4A). Despite the downward trend observed for the index finger, the average individuation index across all digits increased from 0.57 (0.23) to 0.65 (0.20) (paired t-test: p = 0.05) for these participants, although it decreased back to 0.57 (0.18) at the one-month follow-up. Interestingly, there was a shift toward greater MCP flexion to perform the movement, from 39% at the pre-evaluation to 49% at the one-month follow-up.
This preliminary study demonstrated the feasibility of using the AVK system to train fine finger movements. Participants tolerated the system sufficiently that they were able to complete the training sessions without premature withdraw or non-compliance. More importantly, statistically significant changes in multiple outcome measures were observed in this study group, both for measures of impairment (FMH) and measures of task performance (JTHFT). Additionally, change in scores on the ARAT approached the Minimal Clinically Important Difference (MCID) of 5.7 even though our population had a high baseline score which sometimes resulted in a ceiling effect. MCID values have not been established for the other outcome measures employed, but the decrease in time to complete the JTHFT was substantial (30% of the pre-training time). Intriguingly, members of this group also exhibited improved digit individuation, aside from the index finger, following training. The increase in the individuation index was not maintained at follow-up, but the change in strategy favoring greater MCP rotation relative to PIP rotation during individuated finger flexion was maintained. The new ratio could place the digit in a more functional posture during closing.
Improvement in all outcomes was at least as great for the group using the AVK system as for the group receiving intensive, targeted occupational therapy. In fact, for the two measures most closely assessing hand motor control – ARAT and JTHFT – improvements were significantly greater or approaching significance for the group using the AVK system. This was apparent despite the relatively small subject numbers. Outcomes may have been generally better for the Keypad group using the AVK due to the greater number of movements performed. While the OT group practiced a wider variety of motor skills including reaching, grasp-and-release, finger and wrist activities, and fine motor tasks, the Keypad protocol encouraged more repetitions of the same movement task which required constant finger individuation. Indeed, many more key presses (on average 270% more or 700 presses) could be performed, especially in the Song mode, than task-oriented movements completed by the OT group. Merians et. al. and Hesse et. al. have surmised that movement number was a contributor to improvements they observed[12, 31]. Additionally, it is possible that subjects with more mild hand impairment derive greater benefit from intensive practice of distinctive tasks that require continuous refinement of a specific motor skill. Although individuation exercises and tasks were included in the OT protocol, they were under a larger umbrella of tasks addressing the arm, wrist, and fingers both separately and together. Finally, the assistance provided by the PneuGlove may also have contributed to the improvement. By impeding undesired movement of the uninstructed digits, the device allowed users to focus more attention on proper movement of the instructed digits while still providing appropriate proprioceptive feedback.
Interestingly, the Keypad group exhibited a significant decrease in the time needed to complete the manipulation tasks that comprise the JTHFT. Thus, even though none of the tasks practiced during the Keypad treatment (which included no manipulation of real objects) resembled the tasks required in the JTHFT, performance improved considerably after the treatment. This is in agreement with the study of Merians, et al., who observed decreased times for the JTHFT after performing a variety of virtual exercises unrelated to the JTHFT. Together, these results further support the observations of Schaefer, et al., who found generalization in improvement in unpracticed motor tasks after training in other tasks. This generalizability seemingly results from improved motor control rather than learning of a specific task.
Certainly, there were limitations to the generalizability of the results of this study. Overall this preliminary study had relatively low subject numbers that prevented more robust analyses such as repeated measures ANOVA. The initial FMUE scores were slightly higher on average (although not significantly different) for the Keypad group (48.7 ± 9.6) than for the OT group (41.9 ± 1.9). The difference in outcomes between the groups, however, did not appear to arise from differences in initial impairment levels. Little correlation was seen between initial FMUE and change in JTHFT, for example, for either group (Keypad: r = -0.08; OT: r = -0.19). Additionally, initial hand impairment, as measured by the CMSA-H, was closely matched for both groups. All participants were at CH 5 except for one CH 6 in the Keypad group; this subject at CH 6 showed little change with evaluation session across outcome measures. The individuation analyses were performed only on a subset of participants due to technical difficulties. Future studies examining the generalizability of the findings here, such as a randomized controlled trial, are warranted.
The AVK system promotes usage of a variety of digit movements. Certainly some of these movements (e.g., isolated movement of the ring finger) are used much less often than other movements (e.g., movement of the index finger and thumb together) in activities of daily living. Yet, we feel it is important to attempt a variety of tasks in order to explore the movement workspace. For example, a small study was conducted in our laboratory to examine the impact of training pinching forces in the index finger and thumb. Stroke survivors often have difficulty properly directing these forces, such that excessive shear force is created and the object slips from their grasp. Participants were asked to create forces in a variety of directions, not only in the functionally important normal direction. After only a couple of training sessions, pinching force direction improved significantly. These results, together with the results of the current study, suggest that interventions which encourage exploration of all regions of the workspace may be beneficial for rehabilitation.
In summary, training of individuated digit movements was performed with a novel system using a multisensory virtual keypad working in conjunction with an actuated pneumatic glove. Stroke survivors with chronic impairment were able to successfully use the system to improve hand motor control. Thus, repetitive movement therapy for independent finger movements, such as with AVK system, may be beneficial and warrants further exploration.
This work was supported by the National Institute of Disability and Rehabilitation Research (NIDRR) through a Rehabilitation Engineering and Research Center (H133E070013, Machines Assisting Recovery in Stroke). The authors would like to thank Ms. Lynne Rahmeier for transcribing songs for the Keypad format, Ms. Molly L. Corrigan, OTR/L, for performing outcome evaluations, Ms Kathryn Richardson, OTR/L, for subject recruitment and administering OT and Keypad sessions, Ms. Diana Keefe for her initial programming of the GUI and Ms. Kathleen Pacholski for scheduling therapy sessions and overall administrative duties.
- Schieber MH: Individuated finger movements of rhesus monkeys: a means of quantifying the independence of the digits. J Neurophysiol 1991,65(6):1381-1391.PubMedGoogle Scholar
- van Duinen H, Gandevia SC: Constraints for control of the human hand. J Physiol 2011,589(Pt 23):5583-5593.View ArticlePubMedPubMed CentralGoogle Scholar
- Penfield W, Boldrey E: Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain 1937, 60: 389-443. 10.1093/brain/60.4.389View ArticleGoogle Scholar
- Rathelot JA, Strick PL: Muscle representation in the macaque motor cortex: an anatomical perspective. Proc Natl Acad Sci U S A 2006,103(21):8257-8262. 10.1073/pnas.0602933103View ArticlePubMedPubMed CentralGoogle Scholar
- Porter R, Lemon R: Corticospinal function and voluntary movement. Monographs of the Physiological Society. Oxford; New York: Clarendon Press; Oxford University Press; 1993:428. xviiiGoogle Scholar
- Olivier E, Edgley SA, Armand J, Lemon RN: An electrophysiological study of the postnatal development of the corticospinal system in the macaque monkey. J Neurosci 1997,17(1):267-276.PubMedGoogle Scholar
- Lang CE, Schieber MH: Reduced muscle selectivity during individuated finger movements in humans after damage to the motor cortex or corticospinal tract. J Neurophysiol 2004,91(4):1722-1733. 10.1152/jn.00805.2003View ArticlePubMedGoogle Scholar
- Raghavan P, Petra E, Krakauer JW, Gordon AM: Patterns of impairment in digit independence after subcortical stroke. J Neurophysiol 2006,95(1):369-378.View ArticlePubMedGoogle Scholar
- Wenzelburger R, Kopper F, Frenzel A, Stolze H, Klebe S, Brossmann A, Kuhtz-Buschbeck J, Golge M, Illert M, Deuschl G: Hand coordination following capsular stroke. Brain 2005,128(Pt 1):64-74.PubMedGoogle Scholar
- Taheri H, Rowe JB, Gardner D, Chan V, Reinkensmeyer DJ, Wolbrecht ET: Robot-assisted Guitar Hero for finger rehabilitation after stroke. Conf Proc IEEE Eng Med Biol Soc 2012, 2012: 3911-3917.PubMedPubMed CentralGoogle Scholar
- Sale P, Lombardi V, Franceschini M: Hand robotics rehabilitation: feasibility and preliminary results of a robotic treatment in patients with hemiparesis. Stroke Res Treat 2012, 2012: 820931.PubMedPubMed CentralGoogle Scholar
- Merians AS, Fluet GG, Qiu Q, Saleh S, Lafond I, Davidow A, Adamovich SV: Robotically facilitated virtual rehabilitation of arm transport integrated with finger movement in persons with hemiparesis. J Neuroeng Rehabil 2011, 8: 27. 10.1186/1743-0003-8-27View ArticlePubMedPubMed CentralGoogle Scholar
- Lord TJ, Keefe DM, Li Y, Stoykov N, Kamper D: Development of a haptic keypad for training finger individuation after stroke. In International Conference on Virtual Rehabilitation. Zurich, Switzerland; 2011.Google Scholar
- Simone LK, Sundarrajan N, Luo X, Jia Y, Kamper DG: A low cost instrumented glove for extended monitoring and functional hand assessment. J Neurosci Methods 2007,160(2):335-348. 10.1016/j.jneumeth.2006.09.021View ArticlePubMedGoogle Scholar
- Gowland C, Stratford P, Ward M, Moreland J, Torresin W, Van Hullenaar S, Sanford J, Barreca S, Vanspall B, Plews N: Measuring physical impairment and disability with the Chedoke-McMaster stroke assessment. Stroke 1993,24(1):58-63. 10.1161/01.STR.24.1.58View ArticlePubMedGoogle Scholar
- Stoykov ME, Stojakovich M, Towles JD: An occupational therapy protocol for the investigation of cortical stimulation paired with upper limb training. Program No. 181.5, in 2004 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience; 2004. OnlineGoogle Scholar
- Law M, Baptiste S, McColl M, Opzoomer A, Polatajko H, Pollock N: The Canadian occupational performance measure: an outcome measure for occupational therapy. Can J Occup Ther 1990,57(2):82-87. 10.1177/000841749005700207View ArticlePubMedGoogle Scholar
- Guadagnoli MA, Lee TD: Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. J Mot Behav 2004,36(2):212-224. 10.3200/JMBR.36.2.212-224View ArticlePubMedGoogle Scholar
- Lyle RC: A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res 1981,4(4):483-492. 10.1097/00004356-198112000-00001View ArticlePubMedGoogle Scholar
- Beebe JA, Lang CE: Relationships and responsiveness of six upper extremity function tests during the first six months of recovery after stroke. J Neurol Phys Ther 2009,33(2):96-103. 10.1097/NPT.0b013e3181a33638View ArticlePubMedPubMed CentralGoogle Scholar
- Jebsen RH, Taylor N, Trieschmann RB, Trotter MJ, Howard LA: An objective and standardized test of hand function. Arch Phys Med Rehabil 1969,50(6):311-319.PubMedGoogle Scholar
- Fugl-Meyer AR, Jääskö L, Leyman I, Olsson S, Steglind S: The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand J Rehabil Med 1975,7(1):13-31.PubMedGoogle Scholar
- Hager-Ross C, Schieber MH: Quantifying the independence of human finger movements: comparisons of digits, hands, and movement frequencies. J Neurosci 2000,20(22):8542-8550.PubMedGoogle Scholar
- Lang CE, Schieber MH: Differential impairment of individuated finger movements in humans after damage to the motor cortex or the corticospinal tract. J Neurophysiol 2003,90(2):1160-1170. 10.1152/jn.00130.2003View ArticlePubMedGoogle Scholar
- Walker E, Nowacki AS: Understanding equivalence and noninferiority testing. J Gen Intern Med 2011,26(2):192-196. 10.1007/s11606-010-1513-8View ArticlePubMedPubMed CentralGoogle Scholar
- Van der Lee JH, De Groot V, Beckerman H, Wagenaar RC, Lankhorst GJ, Bouter LM: The intra- and interrater reliability of the action research arm test: a practical test of upper extremity function in patients with stroke. Arch Phys Med Rehabil 2001,82(1):14-19. 10.1053/apmr.2001.18668View ArticlePubMedGoogle Scholar
- Shelton FD, Volpe BT, Reding M: Motor impairment as a predictor of functional recovery and guide to rehabilitation treatment after stroke. Neurorehabil Neural Repair 2001,15(3):229-237. 10.1177/154596830101500311View ArticlePubMedGoogle Scholar
- Lang CE, Edwards DF, Birkenmeier RL, Dromerick AW: Estimating minimal clinically important differences of upper-extremity measures early after stroke. Arch Phys Med Rehabil 2008,89(9):1693-1700. 10.1016/j.apmr.2008.02.022View ArticlePubMedPubMed CentralGoogle Scholar
- Chen HM, Chen CC, Hsueh IP, Huang SL, Hsieh CL: Test-retest reproducibility and smallest real difference of 5 hand function tests in patients with stroke. Neurorehabil Neural Repair 2009,23(5):435-440. 10.1177/1545968308331146View ArticlePubMedGoogle Scholar
- Kamper DG, Cruz EG, Siegel MP: Stereotypical fingertip trajectories during grasp. J Neurophysiol 2003,90(6):3702-3710. 10.1152/jn.00546.2003View ArticlePubMedGoogle Scholar
- Hesse S, Werner C, Pohl M, Rueckriem S, Mehrholz J, Lingnau ML: Computerized arm training improves the motor control of the severely affected arm after stroke: a single-blinded randomized trial in two centers. Stroke 2005,36(9):1960-1966. 10.1161/01.STR.0000177865.37334.ceView ArticlePubMedGoogle Scholar
- Schaefer SY, Patterson CB, Lang CE: Transfer of training between distinct motor tasks after stroke: implications for task-specific approaches to upper-extremity neurorehabilitation. Neurorehabil Neural Repair 2013,27(7):602-612. 10.1177/1545968313481279View ArticlePubMedPubMed CentralGoogle Scholar
- Seo NJ, Fischer HW, Bogey RA, Rymer WZ, Kamper DG: Use of visual force feedback to improve digit force direction during pinch grip in persons with stroke: a pilot study. Arch Phys Med Rehabil 2011,92(1):24-30. 10.1016/j.apmr.2010.08.016View ArticlePubMedGoogle Scholar
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