Hand exercise programs that include range of motion (ROM), and strengthening exercises are important compo-nents of non-pharmacological management in people with rheumatoid arthritis (RA) or hand osteoarthritis (HOA) [1-4]. With moderate literature evidence available on the thera-peutic effectiveness of ROM and strength exercises in improving hand function [1-4], a novel task-oriented training using real life object manipulation tasks has been developedfor people with arthritis affecting the hands [5-7]. An innovative computer game-based Tele-rehabilitation platform (TRP) has also been developed in which task-oriented training is coupled with interactive computer gaming [5-7] to increase client motivation and engagement. Using the task- oriented approach, a variety of manipulation tasks with objects of daily life can be practiced while playing computer games [5, 7]. Since home exercise programs are important part of the rehabilitation process, the TRP was designed to extend clinical practice to the home, supported by a clinician. The TRP also includes a telemonitoring application, which is a computer based hand function assessment tool that evaluates task performance during any object manipulation. The telemonitoring module automatically logs clients' task performance measures, and data analyses methods have been developed to quantify task performance during functional object manipulation tasks. These objective outcomes can then be used to track and monitor hand function over repeated sessions [5, 7].

Difficulties in many gross/fine dexterous activities such as opening jar lids, turning door knobs or keys, gripping small objects between finger tips, and holding heavy objects are well documented in RA [8, 9] and HOA [10, 11]. A number of performance based tests are available, such as the Purdue peg board test, nine hole peg test (NHPT) [12, 13], O’Connor Finger Dexterity test [16] Grip Ability Test (GAT) [12], Arthritis Hand Function Test (AHFT) [12-15] and the Jebsen hand function test (JHFT) [12, 13]. These tests measure hand function by the time taken to complete a task. This approach has limited value [12] because, 1) time does not directly relate to performance [20], 2) it is unclear how speed translates into hand use in daily life [17] and 3) speed should not be prioritized over quality [18]. More recently, computer-based hand function assessment tools are being developed which quantify fine/gross motor manipulat-ion skills. For example, Culmera et al [19] developed a standardized hand tracing task that measures both movement duration and spatial-temporal accuracy of fine/gross manipulat-ion skills. However, the above-mentioned tests are limited to a narrow range of objects and tasks, for example: pegs coins, a pen, or kitchen utensils. The pain or stiffness associated with a task was also not considered in any of the test measures. A novel computer based hand function tool has been designed to, 1) provide a standardized method to objectively quantify task performance (movement quality) during manipulation of a broad range of common objects, and 2) evaluate pain and joint stiffness related with each object manipulation task. Reliability and validity of the tool’s test protocol has been demonstrated in asymptomatic individuals [20].

The objectives of the present study were to determine test-retest reliability and convergent validity of the computer based hand function test protocol in people with arthritis. Task performance during three different object manipulation tasks were evaluated. We hypothesized that the performance measures of object manipulation tasks would exhibit high test-retest reliability (ICCs >0.75), and demonstrate moderate correlations (Spearman rho between 0.4 and 0.7) with grip strength, NHPT, DASH and the HAQ. Our secondary object-ives were to evaluate joint pain and stiffness outcomes with three different object manipulation tasks.

With no dropouts assumed, 39 participants were included for ICCs >0.6 with a power of 0.80 and a significance level of 0.05 [21]. A sample size of 30 is considered enough for estimates of reliability and validity, though larger numbers are often preferred [22].

A repeated measures design was used to establish test-retest reliability of the test protocol. Forty participants were recruited through advertisements in local newspapers and rheumatology clinics in Winnipeg. Men and women between 30 and 65 years and diagnosed with RA or HOA were included. People with fixed finger joint deformities, recent upper limb surgeries or trauma (< 6 months), or vision/ hearing problems were excluded. The study was approved by the University of Manitoba Health Research Ethics Board (H2008: 216). Written informed consent was obtained from each participant before evaluation.

A computerized custom visual tracking task with configurable amplitude and frequency designed with a visual target (a bright colored circular cursor) moving sinusoidally in x or y-axis served as a standardized input to guide a manipulation task. The physical components of the tool include a miniature motion sensor (5mm x10mm Minibird model 800, Ascension Technology, Burlington VT, USA) and a hardware interface. Many different objects of daily life can be instrumented with the motion sensor and hence different types of functional tasks can be examined (Table 1). The sensor records the linear and angular position coordinates in the x, y, and z-axes at a sampling rate of 100Hz. The interface allows seamless translation of motion signals from any instrumented object and makes it behave as a standard mouse. The object motions are then used to perform the tracking task (for example: a wineglass tilted up down, as shown in Fig. 1A insert). The moving visual target is set at a frequency of 0.5 Hz and an onscreen amplitude of 15 cm representing optimal motion parameters experienced in daily activities. The position coordinates of the visual target and the motion sensor (user motion) were saved as an electronic file [20]. The tool was also embedded with two separate 0-10 numerical verbal scales for self-reporting of pain and stiffness (Fig. 1B, 1C). These scales appeared in sequence on the computer screen and participants were asked to self-report their pain and stiffness before and after performing the tracking task [20]. The study staff recorded the scores, which were automatically saved with the user motion data [5, 7, 20].

Fig. (1). A. Experimental setup. Participants were comfortably seated before a computer monitor. A plastic wineglass is held with a tripod grip and moved in concert with a sinusoidally moving visual target. The bottom insert shows forward and backward tilting movements of the wine glass on tracking the target moving upward and downward respectively. B. Pain scale. The verbal numerical pain rating scale (0-10) is shown. Blue, green, yellow and red colors depict increasing intensities of pain. C. Stiffness scale. The verbal numerical stiffness rating scale (0-10) is shown. Blue, green, yellow, and red colors depict increasing intensities of stiffness. D. Reference and user movement trajectories. The bold lined waveform represents the user trajectory and the light shaded waveform is the reference trajectory. Y-axis represents screen amplitude and the x-axis represents time in seconds.

Fig. (2). a. User movement trajectory plots for all three tasks. The user trajectory plots for wineglass, salad tongs, and jug tasks are shown. The top panel of plots represent user trajectories with COD’s >0.80 and bottom panel with COD’s <0.5. The maximum and minimum boundaries of reference waveform are highlighted by horizontal lines above and below each user trajectory. b. Mean and standard error of mean for COD of each task. Histograms of mean and standard error of mean for COD of wineglass (WG), salad tongs (ST) and jug (JG) tasks in test sessions 1 (grey bars) and 2 (black bars). COD measured from 0-1, is represented on the y-axis.

Fig. (3). A. Pre/post pain in each task. The box and whisker plot shows pain scores for each task. The Y-axis represents the pain scores on (0-10) scale. The upper and lower parts of the boxes represent the upper and lower quartiles and the median is presented as the middle line. The upper and lower whiskers are the maximum and minimum values, * significance p<0.05. B. Pre/post stiffness in each task. The box and whisker plot shows stiffness scores for each task. The Y-axis represents the stiffness scores on (0-10) scale. The upper and lower parts of the boxes represent the upper and lower quartiles and the median is presented as the middle line. The upper and lower whiskers are the maximum and minimum values, *significance p<0.05.

The first test session included administration of grip strength test; NHPT and DASH in the same order, before evaluating the three object tasks. Grip strength of the dominant hand was tested using an isometric hand dynamometer (G100, Biometrics Ltd., UK) in the testing position recommended by American Society of Hand Therapists [23, 24]. Participants gripped the dynamometer as hard as possible once without any jerking. The best score out of three consecutive trials was used for analyses. Sufficient time was allowed for the participants to recover from any fatigue related to grip testing. Fine finger dexterity was then assessed by the time taken for placement and removal of nine pegs in the pegboard using the NHPT [25]. Participants also completed the DASH [26, 27], which contains 30 items on disability/symptoms related to upper limb activities. Level of difficulty in performing each item is rated on a 1-5 point scale (1- no difficulty and 5- unable to do). Scores range between 0-100 with higher scores indicating greater disability.

Fig. (1) illustrates the experimental setup, and the pain and stiffness scales. The participant was comfortably seated before a computer monitor positioned at eye level. The arm was positioned with the shoulder flexed at 60 degrees and internally rotated, elbow flexed and forearm supported on a 15-inch Styrofoam block. A strap around the wrist allowed free hand movements in the air. The objects included a long stem plastic wineglass, salad tongs and a jug half filled with water. These objects represent a wide range of physical properties requiring different modes of manipulation such as tripod grip, thumb opposition, and whole hand grasp respectively. In both test sessions, the motion sensor was secured on a same point marked on the mid portion of the wineglass bowl; the top arm of the salad tongs and on the mid portion of the jug’s front surface (opposite to handle). Manipulation of the wineglass required a tripod grip involving the thumb, index, and middle fingers. The wineglass held at the stem was tilted forward down (away from the body) and straight up to vertical (towards the body), bottom insert of Fig. (1A). The task involved thumb opposition and interphalangeal (IP) flexion, index finger abduction, metacarpophalangeal (MCP) flexion, rotation and IP flexion or extension of index and middle fingers, and ulnar/radial deviations. The other two fingers could flex or extend. Manipulation of the salad tongs involved full open-ing and closing of the two arms together with the vertical movements of the visual target. They were held with the thumb placed on the top arm while the index and middle fingers held the lower arm. The task involved thumb extension, adduction/abduction MCP and IP flexion/extens-ion at the second and third digits. The jug was held with a power grasp and tilted left and right along the horizontally moving target. With the forearm in the mid prone position, the task included supination/pronation, and flexion at the MCP, IP joints of all fingers and the thumb in extension. The motion was restricted to the wrist and forearm while the fingers provided a stable grip. Three to five minutes of transition time was allowed before the next consecutive task. All of the participants were provided with a demonstration before testing. After one practice trial, each task was evaluated for 20 seconds, which produced 12 movement cycles.

A week later, the HAQ questionnaire [28, 29] which measures difficulties in daily activities using a 0-3 point scale (0- without difficulty, 3- unable to do), was completed. The same assessor then evaluated the three tasks in the same order.

Demographic characteristics and the scores (Mean ±SD) of grip strength, NHPT, DASH and HAQ of the study participants are presented in Table 2. Fig. (2a) presents representative examples (and respective CODs) of the user motion trajectories with the three tasks. The top panels of plots are examples of good performance (CODs > 0.8) and the bottom panels, of poor performance (CODs <0.5). Fig. (2b) presents the mean (standard error) for the COD of each task during both test sessions. Table 3 presents the group means (SD) for COD, ICCs, and SEMs. Test re-test reliability of the task performance was high (ICC >0.75) for wineglass task and moderate (ICC between 0.5 and 0.75) for the jug and salad tongs tasks. Paired student’t’ tests showed no significant differences in mean performance measures for each task between the sessions (p>0.05).

Table 4 presents the ‘rho’ values reported between 1) task performance measures of wineglass, salad tongs, and jug manipulations with grip strength, NHPT, DASH, and HAQ, 2) task performance measures of wineglass, salad tongs, and jug manipulations, and 3) grip strength, NHPT, DASH, and HAQ. The HAQ was moderately correlated with the task performance measures of wineglass and jug tasks but had low correlations with salad tongs task. Low correlations were observed between all task performance measures and grip strength, NHPT and the DASH, and between the task performance measures of three objects themselves. Moderate correlations were seen between the DASH and HAQ; and between grip strength, DASH, and HAQ respectively.

Fig. (3A, 3B) presents the box and whisker plots for group median and Interquartile range (IQR) for pain and stiffness scores reported before and after each task. There was significant reduction in pain and stiffness levels after each task in both test sessions (p<0.05).

The study purpose was to determine Test-retest reliability and convergent validity of a computer based hand function test protocol in people with arthritis. Test-retest reliability of performance measures during manipulation of three common objects (wineglass, salad tongs, and jug) ranged from high to moderate. In general, we observed low correlations between the task performance measures and grip strength, NHPT, DASH and HAQ. Exceptions were moderate correlations between the wineglass and jug task performance measures with the HAQ. In addition, performance measures between the objects demonstrated low correlations with each other. Interestingly, there was a significant reduction in joint pain and stiffness after performing each task.

Concerning the grip strength been considered for construct validity, it is often an important outcome of hand rehabilitation programs and has been evaluated as a proxy measure for hand function in many studies involving rheumatoid and osteoarthritis populations [50-58]. The DASH questionnaire was considered for: 1) the questionnaire items focus on impairments, activity limitations, and participation restrictions, which are the three constructs of the Internatio-nal Classification of Functioning Disability and Health (ICF) taxonomy model, 2) compared to other upper limb self-report questionnaires, the DASH has excellent psychometric proprieties in a wide variety of upper limb conditions [26, 59-61], 3) it is also being extensively used in clinical practice and research in rheumatoid and osteoarthritis popu-lations [61], and, 4) administration and respondent burden to complete the questionnaire is minimal. The approximate time for administration and scoring were 10-15, and five minutes respectively. However, as the DASH questionnaire represent limited number of hand function related tasks in daily life, it would of benefit and meaningful to include other self-report measures such as Patient Rated Wrist Hand Evaluation (PRWHE) [26, 27, 61], and Michigan Hand Out-comes Questionnaire (MHQ) [15] in future studies. Both cover specific domains of hand function such as difficulties in performing activities of daily life, pain, aesthetics, and satisfaction and hence might be considered for validity evaluation of the computer game based hand function tool.

The potential contribution of the novel measure is that it provides an objective measurement of overall performance of any object manipulation task. While other objective hand function measures the time taken to complete a task as a surrogate for hand function, the novel tool analyses the entire movement trajectory of a manipulation task to provide direct outcome of the performance. Evaluation of the tool measure in three different objects has provided valuable evidence on the feasibility of the protocol and initial data on the COD, pain, and stiffness scores. The tool should be tested further in other manipulation tasks that have been documented difficult to perform in people with arthritis hands, for example, opening a jar lid, pouring activity, and carrying heavy weights etc. Future modifications in the final protocol would include a heterogeneous study sample, tracking of pain medication data, and repeated testing of the tool measure in many number of manipulation tasks and validating with other comparative hand function measures in hand osteoarthritis and rheumatoid arthritis populations.

According to the International Classification of Functioning, Disability, and Health (ICF) framework, the impact of a health condition on an individual can be classified through Body Structure/Function and Activities and Participation, which are further influenced by environmental/personal factors [62]. Measurement of function and life-role participation interact [63] and many agree that we should measure at each level in order to determine which interventions that result in gains in task skills and function also result in sufficient improvements in life role participation [63, 64]. For example how and to what extent does increased strength, or movement quality of fine/gross object manipulation tasks improve an individual’s ability to manage housework, go shopping, use an ATM card or participate in various leisure and social activities. There is also a definite need to develop tools to identify and delineate outcomes and parameters of rehabilitation programs [65], which could be used to track changes over time and make informed decisions about efficacy and dose response relationships [66, 67]. The computer based assessment tool allows a within subject analysis and trends could be identified with even larger variations in performance measures. In addition, hand function cannot be graded with just one task; therefore testing of many several common objects should be included. A pilot randomized trial [7], in which the present tool is used as an exploratory outcome measure has been completed.

The computer based hand assessment tool provides a standardized method to evaluate task performance during any object manipulation task. This approach allows one to focus not only on body functions and on structures but also on outcomes related to activity and participation; and movement precision that is a critical factor for efficient performance. Many different objects of daily life can be used and thus performance with different types of manipulation tasks can be objectively quantified with the tool. Knowledge of the object properties and functional demands allows therapists to target specific treatment goals such as graded joint mobility, endurance, strength, and dexterity. In this way, the tool can also be used for task-oriented training with real life objects and personalized training goals in order to improve hand function in daily life.