Pronation and supination analysis based on biomechanical signals from Parkinson’s disease patients

The Correlation Between Reach and Grasp Kinematic Measures and Clinical Measures of Manual Dexterity in Patients With Parkinson Disease

“…Although it seems that laboratory measures such as kinematic parameters determined by motion analysis system are more representative of motor control strate-gies, only a few studies have evaluated the relationship between upper limb kinematic parameters and clinical data. Also these studies were limited to the subjects with stroke [9][10][11]. Only recently, Garza Rodriguez et al reported a significant correlation between kinematic measures of supination and pronation and clinical assessment of supination/pronation using item 3.6 of the Unified Parkinson's Disease Rating Scale (UPDRS) [12].…”

An Expert System for Quantification of Bradykinesia Based on Wearable Inertial Sensors

“…Bradykinesia is evaluated using repetitive hand and leg movements, such as finger-tapping, hand opening/closing, pronation/supination, and foot (or toe) tapping [2]. As a part of the examination, patients are requested to repeatedly perform specified movements, as fast and with the biggest amplitude as possible, during some short period of time, usually 10–15 s [4,5,6,7], or for some specified number of repetitions, e.g., 10 times [8,9,10]. These movements are evaluated based on specifically defined criteria, including speed, amplitude, amplitude decrement, and number of hesitations or freezes.…”

“…They are expensive and require dedicated space for recording (they are bulky), which significantly limits their applicability in clinical settings [13]. Due to these limitations, wearable systems, such as smartphones [14], magnetic sensors [13], and inertial measurement units (IMUs) [7,8,9,15,16,17,18,19,20], are increasingly being applied for bradykinesia assessment. IMUs are small, lightweight, easy to mount, and do not require dedicated space for recording, which makes them more suitable for fast and reliable everyday clinical applications.…”

“…In the literature, bradykinesia is assessed by analysing different repetitive movements, including finger-tapping [8,13,21], hand opening/closing [16,17], hand pronation/supination [9,10,22], and toe tapping [23], as well as by simultaneous analysis of different movements [12,20,24]. From finger-tapping (FT) accelerometer data, researchers extract different features, describing the frequency and biomechanical properties of the movements, and use them as input into the ordinal logistic regression model for prediction of UPDRS FT scores [8].…”

“…Decision rules can be designed to match exactly the criteria of the decision-making process and instructions applied in clinical practice. Fuzzy rules were applied for prediction of clinical scores using inertial data recorded during foot tapping [23] and hand pronation/supination movements in [9]. Their designed rules provide good results, with an accuracy of about 90%.…”