The development of a novel grip motion analysis technique using the Dartfish movement analysis software to evaluate hand movements during activities of daily living

Using active or functional range of motion as a further indicator to detect hand osteoarthritis. A preliminary study

PURPOSE

Propose further indicators for helping to detect hand osteoarthritis (HOA) using either active or functional ranges of motion (AROM or FROM).

METHOD

Hand kinematics data of 16 hand joint angles from previous studies were used, taken from healthy participants and HOA patients with differently affected joints and distinct levels of compromise. Data consisted of: (i) AROM (extreme values and ranges); (ii) FROM while performing the Sollerman Hand Function Test (mean, extreme percentiles and ranges). Two linear discriminant analyses (stepwise method) were conducted, one per dataset (AROM and FROM), with condition (healthy/patient) as the grouping variable. The potential predictors were the data from the joints with significant differences between samples for each analysis (A-predictors and F-predictors).

RESULTS

Good sensitivity-specificity values of 85.2-90.9% and 93.8-93.9% for F-predictors and A-predictors, respectively. Sets of predictors corresponded to the joints more commonly affected by HOA. F-predictors: lower maximal flexion of carpometacarpal and interphalangeal thumb joints, higher maximal flexion of thumb metacarpal joint, lower flexion/extension range of ring proximal interphalangeal joint and higher maximal little finger adduction. A-predictors: narrower flexion/extension range of the thumb carpometacarpal joint, lesser extension of the ring metacarpophalangeal joint; lower flexion of the middle finger proximal interphalangeal joint along with a narrower palmar arch range.

CONCLUSION

Both sets of predictors provide discrimination capacity of HOA with good sensitivity-specificity, slightly better for A-predictors. The AROM measurement is technically less demanding and can be clinically applied even with manual goniometry.

Hand kinematics in osteoarthritis patients while performing functional activities

PURPOSE

To identify the impact of kinematic limitations on hand osteoarthritis patients' ability to perform daily living activities.

METHODS

An experiment was performed on 33 patients and 32 healthy subjects. Active ranges of motion (AROM) of 16 hand joint angles were measured, together with scores of different hand tests of dexterity (Box and Block, Nine Hole Peg, Kapandji) and function (Sollerman Hand Function Test, SHFT). Functional ranges of motion (FROM) were recorded during SHFT tasks. Results by task are also reported.

RESULTS

Patients' AROM is limited in flexion of thumb carpometacarpal and interphalangeal, and finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints, and in palmar arch. Patients scored worse in gross dexterity and opposition, but only Kapandji score was correlated with AROM limitations. Pain is mostly reported in patients with limited extension of finger MCP and PIP joints. Patients used significantly different FROM in almost all the joints, and needed more time to accomplish the SHFT tasks.

CONCLUSIONS

AROM measurements can be used as indicators for early diagnosis. Patients use specific strategies to accomplish each task, arising from AROM limitations; some tasks with very extreme postures. The tasks where precision or force are required for thumb are the most affected ones.Implications for rehabilitationActive range of motion is an indicator for early hand osteoarthritis diagnosis.Patients' functional ranges are reduced, and thumb opposition and gross dexterity are hindered.Rehabilitation should focus especially on tasks requiring precision and thumb strength.Rehabilitation should favor the improvement of task completion times.

Using Sensorized Gloves and Dimensional Reduction for Hand Function Assessment of Patients with Osteoarthritis

Sensorized gloves allow the measurement of all hand kinematics that are essential for daily functionality. However, they are scarcely used by clinicians, mainly because of the difficulty of analyzing all joint angles simultaneously. This study aims to render this analysis easier in order to enable the applicability of the early detection of hand osteoarthritis (HOA) and the identification of indicators of dysfunction. Dimensional reduction was used to compare kinematics (16 angles) of HOA patients and healthy subjects while performing the tasks of the Sollerman hand function test (SHFT). Five synergies were identified by using principal component (PC) analyses, patients using less fingers arch, higher palm arching, and a more independent thumb abduction. The healthy PCs, explaining 70% of patients’ data variance, were used to transform the set of angles of both samples into five reduced variables (RVs): fingers arch, hand closure, thumb-index pinch, forced thumb opposition, and palmar arching. Significant differences between samples were identified in the ranges of movement of most of the RVs and in the median values of hand closure and thumb opposition. A discriminant function for the detection of HOA, based in RVs, is provided, with a success rate of detection higher than that of the SHFT. The temporal profiles of the RVs in two tasks were also compared, showing their potentiality as dysfunction indicators. Finally, reducing the number of sensors to only one sensor per synergy was explored through a linear regression, resulting in a mean error of 7.0°.

Evaluation of Optical and Radar Based Motion Capturing Technologies for Characterizing Hand Movement in Rheumatoid Arthritis-A Pilot Study

In light of the state-of-the-art treatment options for patients with rheumatoid arthritis (RA), a detailed and early quantification and detection of impaired hand function is desirable to allow personalized treatment regiments and amend currently used subjective patient reported outcome measures. This is the motivation to apply and adapt modern measurement technologies to quantify, assess and analyze human hand movement using a marker-based optoelectronic measurement system (OMS), which has been widely used to measure human motion. We complement these recordings with data from markerless (Doppler radar) sensors and data from both sensor technologies are integrated with clinical outcomes of hand function. The technologies are leveraged to identify hand movement characteristics in RA affected patients in comparison to healthy control subjects, while performing functional tests, such as the Moberg-Picking-Up Test. The results presented discuss the experimental framework and present the limiting factors imposed by the use of marker-based measurements on hand function. The comparison of simple finger motion data, collected by the OMS, to data recorded by a simple continuous wave radar suggests that radar is a promising option for the objective assessment of hand function. Overall, the broad scope of integrating two measurement technologies with traditional clinical tests shows promising potential for developing new pathways in understanding of the role of functional outcomes for the RA pathology.