Performance evaluation of metaheuristics-tuned recurrent neural networks for electroencephalography anomaly detection.

Electroencephalography (EEG) serves as a diagnostic technique for measuring brain waves and brain activity. Despite its precision in capturing brain electrical activity, certain factors like environmental influences during the test can affect the objectivity and accuracy of EEG interpretations. Challenges associated with interpretation, even with advanced techniques to minimize artifact influences, can significantly impact the accurate interpretation of EEG findings.

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

Wearable sensors and advanced algorithms can provide significant decision support for clinical practice. Currently, the motor symptoms of patients with neurological disorders are often visually observed and evaluated, which may result in rough and subjective quantification. Using small inertial wearable sensors, fine repetitive and clinically important movements can be captured and objectively evaluated.

Selection of gait parameters for differential diagnostics of patients with de novo Parkinson's disease.

Background: Gait disturbances are an integral part of clinical manifestations of Parkinson's disease (PD), even in the initial stages of the disease. Our goal was to identify the set of spatio-temporal gait parameters that bear the highest relevance for characterizing de novo PD patients.

Methods: Forty patients with de novo PD and forty healthy controls were recorded while walking over an electronic walkway in three different conditions: (1) base walking, (2) walking with an additional motor task, (3) walking with an additional mental task.

Quantification of Finger-Tapping Angle Based on Wearable Sensors.

We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns.

Finger tapping analysis in patients with Parkinson's disease and atypical parkinsonism.

The goal of this study was to investigate repetitive finger tapping patterns in patients with Parkinson's disease (PD), progressive supranuclear palsy-Richardson syndrome (PSP-R), or multiple system atrophy of parkinsonian type (MSA-P). The finger tapping performance was objectively assessed in PD (n=13), PSP-R (n=15), and MSA-P (n=14) patients and matched healthy controls (HC; n=14), using miniature inertial sensors positioned on the thumb and index finger, providing spatio-temporal kinematic parameters. The main finding was the lack or only minimal progressive reduction in amplitude during the finger tapping in PSP-R patients, similar to HC, but significantly different from the sequence effect (progressive decrement) in both PD and MSA-P patients.

Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface.

Brain-computer interfaces (BCIs) have the potential to improve functionality in chronic stoke patients when applied over a large number of sessions. Here we evaluated the effect and the underlying mechanisms of three BCI training sessions in a double-blind sham-controlled design. The applied BCI is based on Hebbian principles of associativity that hypothesize that neural assemblies activated in a correlated manner will strengthen synaptic connections.

Quantitative and qualitative gait assessments in Parkinson's disease patients.

Background/aim: Postural impairments and gait disorders in Parkinson's disease (PD) affect limits of stability, impaire postural adjustment, and evoke poor responses to perturbation. In the later stage of the disease, some patients can suffer from episodic features such as freezing of gait (FOG). Objective gait assessment and monitoring progress of the disease can give clinicians and therapist important information about changes in gait pattern and potential gait deviations, in order to prevent concomitant falls.

Automatic identification and classification of freezing of gait episodes in Parkinson's disease patients.

Alternation of walking pattern decreases quality of life and may result in falls and injuries. Freezing of gait (FOG) in Parkinson's disease (PD) patients occurs occasionally and intermittently, appearing in a random, inexplicable manner. In order to detect typical disturbances during walking, we designed an expert system for automatic classification of various gait patterns.

Nonlinear optimization for drift removal in estimation of gait kinematics based on accelerometers.

A new data processing method is described for estimation of angles of leg segments, joint angles, and trajectories in the sagittal plane from data recorded by sensors units mounted at the lateral side of leg segments. Each sensor unit comprises a pair of three-dimensional accelerometers which send data wirelessly to a PC. The accelerometer signals comprise time-varying and temperature-dependent offset, which leads to drift and diverged signals after integration.

Kinematics of gait: new method for angle estimation based on accelerometers.

A new method for estimation of angles of leg segments and joints, which uses accelerometer arrays attached to body segments, is described. An array consists of two accelerometers mounted on a rigid rod. The absolute angle of each body segment was determined by band pass filtering of the differences between signals from parallel axes from two accelerometers mounted on the same rod.

Sensor-driven four-channel stimulation of paretic leg: functional electrical walking therapy.

This study introduces a Functional Electrical Therapy (FET) system based on sensor-driven electrical stimulation for the augmentation of walking. The automatic control relates to the timing of stimulation of four muscles. The sensor system comprises accelerometers and force-sensing resistors.