Classification Models of Action Research Arm Test Activities in Post-Stroke Patients Based on Human Hand Motion.

The Action Research Arm Test (ARAT) presents a ceiling effect that prevents the detection of improvements produced with rehabilitation treatments in stroke patients with mild finger joint impairments. The aim of this study was to develop classification models to predict whether activities with similar ARAT scores were performed by a healthy subject or by a subject post-stroke using the extension and flexion angles of 11 finger joints as features. For this purpose, we used three algorithms: Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN). The dataset presented class imbalance, and the classification models presented a low recall, especially in the stroke class. Therefore, we implemented class balance using Borderline-SMOTE. After data balancing the classification models showed significantly higher accuracy, recall, f1-score, and AUC. However, after data balancing, the SVM classifier showed a higher performance with a precision of 98%, a recall of 97.5%, and an AUC of 0.996. The results showed that classification models based on human hand motion features in combination with the oversampling algorithm Borderline-SMOTE achieve higher performance. Furthermore, our study suggests that there are differences in ARAT activities performed between healthy and post-stroke individuals that are not detected by the ARAT scoring process.

Quantitative Assessment of Hand Function in Healthy Subjects and Post-Stroke Patients with the Action Research Arm Test.

The Action Research Arm Test (ARAT) can provide subjective results due to the difficulty assessing abnormal patterns in stroke patients. The aim of this study was to identify joint impairments and compensatory grasping strategies in stroke patients with left (LH) and right (RH) hemiparesis. An experimental study was carried out with 12 patients six months after a stroke (three women and nine men, mean age: 65.2 ± 9.3 years), and 25 healthy subjects (14 women and 11 men, mean age: 40.2 ± 18.1 years. The subjects were evaluated during the performance of the ARAT using a data glove. Stroke patients with LH and RH showed significantly lower flexion angles in the MCP joints of the Index and Middle fingers than the Control group. However, RH patients showed larger flexion angles in the proximal interphalangeal (PIP) joints of the Index, Middle, Ring, and Little fingers. In contrast, LH patients showed larger flexion angles in the PIP joints of the Middle and Little fingers. Therefore, the results showed that RH and LH patients used compensatory strategies involving increased flexion at the PIP joints for decreased flexion in the MCP joints. The integration of a data glove during the performance of the ARAT allows the detection of finger joint impairments in stroke patients that are not visible from ARAT scores. Therefore, the results presented are of clinical relevance.

Hand Motion Analysis during the Execution of the Action Research Arm Test Using Multiple Sensors.

The Action Research Arm Test (ARAT) is a standardized outcome measure that can be improved by integrating sensors for hand motion analysis. The purpose of this study is to measure the flexion angle of the finger joints and fingertip forces during the performance of three subscales (Grasp, Grip, and Pinch) of the ARAT, using a data glove (CyberGlove II®) and five force-sensing resistors (FSRs) simultaneously. An experimental study was carried out with 25 healthy subjects (right-handed). The results showed that the mean flexion angles of the finger joints required to perform the 16 activities were Thumb (Carpometacarpal Joint (CMC) 28.56°, Metacarpophalangeal Joint (MCP) 26.84°, and Interphalangeal Joint (IP) 13.23°), Index (MCP 46.18°, Index Proximal Interphalangeal Joint (PIP) 38.89°), Middle (MCP 47.5°, PIP 42.62°), Ring (MCP 44.09°, PIP 39.22°), and Little (MCP 31.50°, PIP 22.10°). The averaged fingertip force exerted in the Grasp Subscale was 8.2 N, in Grip subscale 6.61 N and Pinch subscale 3.89 N. These results suggest that the integration of multiple sensors during the performance of the ARAT has clinical relevance, allowing therapists and other health professionals to perform a more sensitive, objective, and quantitative assessment of the hand function.

Intra-rater reliability and diagnostic accuracy of a new vaginal dynamometer to measure pelvic floor muscle strength in women with urinary incontinence.

AIMS: The first choice treatment in urinary incontinence (UI) is rehabilitation of the pelvic floor in order to improve muscle strength. However, no entirely reliable instruments for quantifying pelvic floor muscle (PFM) strength are currently available. Our aim was to test the intra-rater reliability and diagnostic accuracy of a new vaginal dynamometer for measuring PFM strength. METHODS: Test-retest reliability study. One hundred and four women with stress urinary incontinence (SUI) were recruited. Patients were excluded if they had a history consistent with urge urinary incontinence or pelvic organ prolapse, pregnancy, previous urogynecological surgery, severe vaginal atrophy, or neurological conditions. The examination comprised digital palpation quantified by the modified Oxford scale and by two consecutive dynamometry measurements obtained using a new prototype dynamometer. This instrument comprises a speculum in which an inductive displacement sensor (LVDTSM210.10.2.KTmodel, Schreiber) is attached to a spring of known stiffness constant (k). The intraclass correlation coefficient (ICC) was calculated to assess intra-rater reliability. Diagnostic accuracy was assessed using Receiver Operating Characteristics (ROC) curves analysis. RESULTS: Of the 104 subjects included, 59.6% presented scores between 0-2 on the Oxford scale. Intra-rater reliability was 0.98 (95%CI: 0.97-0.99). In the Bland & Altman plot, the distribution of disagreements was similar in the lowest and the highest strength values. The diagnostic accuracy of the dynamometer with regard to digital palpation showed an area under the curve of 0.85 (95%CI: 0.77-0.93). CONCLUSIONS: Our results suggest that this new vaginal dynamometer is a reliable and valid instrument for quantifying PFM strength. Neurourol. Urodynam. 36:333-337, 2017. © 2015 Wiley Periodicals, Inc.

Reliability and Diagnostic Accuracy of a New Vaginal Dynamometer to Measure Pelvic Floor Muscle Strength.

AIMS: Assess the intrarater and interrater reliabilities and diagnostic accuracy of a new vaginal dynamometer to measure pelvic floor muscle (PFM) strength in incontinent and continent women. METHODS: A test-retest reliability study including 152 female patients. EXCLUSION CRITERIA: history of urge urinary incontinence, prolapse of pelvic organ, pregnancy, previous urogynecological surgery, severe vaginal atrophy, or neurological conditions. The examination comprised digital assessment using the modified Oxford scale (MOS) and dynamometry measurements with a new prototype hand-held dynamometer. The MOS score ranges from 0 to 5: 0, no contraction; 1, flicker; 2, weak; 3, moderate; 4, good; 5, strong. Examinations were performed by a physiatrist, a physiotherapist and a midwife. The rest period between each rater measurement was 5 minutes. Assessment of intrarater and interrater reliability was calculated with the intraclass correlation coefficient. RESULTS: One hundred twenty-two incontinent women and 30 continent women were included. Scores between 0 and 2 in MOS were recorded in 72% of incontinent women versus 20% in continent patients (P < 0.001). Intrarater reliability of the dynamometer was 0.942 (95% confidence interval [CI], 0.920-0.958) and the interrater reliability was 0.937 (95% CI, 0.913-0.954). The analysis of variance analysis showed significant differences in PFM strength across digital assessment categories. The post-hoc analysis showed statistical differences between adjacent categories of MOS 1-2 and 2-3. The diagnostic accuracy showed an area under the curve of 0.82 (95% C,: 0.75-0.89), 0.87 (95% CI, 0.81-0.92), and 0.83 (95% CI, 0.77-0.90) for the physiatrist, midwife, and physiotherapist, respectively. CONCLUSIONS: The results obtained show a good reliability and validity of this new vaginal dynamometer to quantify PFM strength.

Virtual human hand: model and kinematics.

The human hand plays an important role in daily life. It is the interface between the human and the exterior world by positioning, orienting, touching and grasping objects. The human hand has multiple degrees of freedom (DOFs) to enable mobility and dexterity. A virtual human hand model can be inserted into CAD (Computer Aided Design) models to assess the manipulation capabilities in the early design stage to reduce design time and cost. Joystick assessment is one of the important design cases. This study is a first step towards a comprehensive hand simulation tool to simulate the manipulation and grasping of objects. This paper presents a novel 25 DOFs' hand skeletal model based on hand anatomy and hand kinematics: (1) joint range of motion, (2) Denavit-Hartenberg method to define the joint relationship and (3) finger workspace determination. Novelty for this hand model includes arching the palm with the four DOFs added in the carpometacarpal and wrist joints for the ring and small fingers.

Effect of human link length determination on posture reconstruction.

Motion capture experiment results are often used as a means of validation for digital human simulations. Motion capture results are marker positions and joint centers in Cartesian space. However, joint angles are more intuitive and easy to understand compared to marker or joint center positions. Posture reconstruction algorithms are used to map Cartesian space to joint space by re-creating experimental postures with simulation models. This allows for direct comparison between the experimental results and digital human simulations. Besides the inherent experimental errors from motion capture system, one source of simulation error is the determination of the link lengths to be used in the simulation model. The link length errors can propagate through all simulation results. Therefore, it is critical to eliminate the link length errors. The objective of this study is to determine the best method of determining link lengths for the simulation model to best match the model to the experiment results containing errors. Specifically, the way that the link lengths are calculated in the posture reconstruction process from motion capture data has a significant effect on the recreated posture for the simulation model. Three link length calculation methods (experimental-average method, trial-specific method, and T-pose method) are developed and compared to a benchmark method (frame-specific method) for calculating link lengths. The results indicate that using the trial-specific method is the most accurate method when referring to calculating frame-specific link lengths.

A light weight compliant hand mechanism with high degrees of freedom.

This paper presents the design and prototyping of an inherently compliant lightweight hand mechanism. The hand mechanism itself has 15 degrees of freedom and five fingers. Although the degrees of freedom in each finger are coupled, reducing the number of independent degrees of freedom to 5, the 15 degrees of freedom of the hand could potentially be individually actuated. Each joint consists of a novel flexing mechanism that is based on the loading of a compression spring in the axial and transverse direction via a cable and conduit system. Currently, a bench top version of the prototype is being developed; the three joints of each finger are coupled together to simplify the control system. The current control scheme under investigation simulates a control scheme where myoelectric signals in the wrist flexor and extensor muscles are converted in to x and y coordinates on a control scheme chart. Static load-deformation analysis of finger segments is studied based on a 3-dimensional model without taking the stiffener into account, and the experiment validates the simulation.