Validação de uma órtese de punho instrumentada para avaliação da rigidez em pessoas com a doença de Parkinson

Abstract

Introduction and Literature Review: Parkinson's Disease (PD) is a neurological condition that impacts mobility, affecting millions of people. It presents both motor and non-motor signs and symptoms, with the four cardinal features being tremor, bradykinesia, postural instability, and rigidity, which is the focus of this study. Diagnosis is made through clinical analysis if the patient exhibits at least two of these signs and symptoms, with the Movement Disorder Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS) serving as the gold standard, albeit a subjective method. Physiotherapeutic processes have shown validity in treating PD symptoms, often employing robotic technologies. Notable among these are inertial measurement units (IMU), elastography, myotonometry, and servo motors. This present work aims to validate the use of an orthosis to assist in the objective quantification of rigidity in PD patients using force, current, and angular displacement data obtained from a linear motor, thus potentially aiding the field of physiotherapy, particularly in the context of treatment and monitoring of the pathology. Methodology: The orthosis used was developed at the Center for Innovation and Technological Evaluation in Health (NIATS) and is electronically composed of the linear motor LM 2070-080-11 and the microcontroller MCLM 3006 S RS (Faulhaber, Germany). The validation process focused on the current consumed by the actuator, the force exerted by it, and the angular displacement caused at the wrist. The Faulhaber Motion Manager software (providing the current consumed by the motor and the displacement of the rod) and RStudio were utilized. The manufacturer provides a force constant in the actuator's datasheet, but it was necessary to verify its validity. To calibrate the force exerted by the actuator, an experiment was proposed using various masses attached to the actuator by a pulley. This allowed calculating the weight force for each mass and comparing it with the force estimated based on the current consumed by the motor, thus creating a calibration curve between the real force and the estimated force, as well as calculating a new force constant. For the calibration of the wrist's angular displacement, the GP_10 goniometer and Myosystem-Br1 software were used. Two protocols were established: the first involved displacing the rod in increments of 1000, measuring the angular displacement for each position of the rod; the second protocol displaced the rod between its minimum and maximum positions, concurrently capturing data from the goniometer. This way, a calibration curve was created based on the displacement values of the rod and the values from the goniometer. Results: Regarding the calibration of the force exerted, the calculated force constant was 14.28 N/A, 18.49% higher than the manufacturer's provided value (11.64 N/A), with a Pearson correlation coefficient of 0.9997189. The minimum mass detected by the actuator was 39.07 grams, and the maximum mass it could support without yielding was 812.64 grams. As for the angular displacement, both methodologies showed linearity between the analyzed variables, with Pearson coefficients of 0.9995091 and 0.995259, respectively, with variations between the parameters of the calibration curves, reinforcing the validity of both methods. Conclusion: The statistical metrics obtained in the proposed methodologies reinforce the validity of the proposed models, even if occasional adjustments or improvements are necessary, making them significantly helpful in the field of physiotherapy.