Ferdinan Widjaja

Functional electrical stimulation in rehabilitation engineering: a survey

Functional electrical stimulation (FES) is used widely in rehabilitation to restore motor functions for paralyzed patients. This paper makes a comprehensive review on current situation of FES. The content includes stimulation interface, applications, FES control, challenges and prospect of FES. Especially, combination FES with electromyography (EMG) and brain computer interface (BCI) is surveyed.

Pattern Mining of Multichannel sEMG for Tremor Classification

Tremor is defined as the involuntary rhythmic or quasi-rhythmic oscillation of a body part, resulting from alternating or simultaneous contractions of antagonistic muscle groups. While tremor may be physiological, those who have disabling pathological tremors find that performing typical activities for daily living to be physically challenging and emotionally draining. Detecting the presence of tremor and its proper identification are crucial in prescribing the appropriate therapy to lessen its deleterious physical, emotional, psychological, and social impact. While diagnosis relies heavily on clinical evaluation, pattern analysis of surface electromyogram (sEMG) signals can be a useful diagnostic aid for an objective identification of tremor types. Using sEMG system attached to several parts of the patients body while performing several tasks, this research aims to develop a classifier system that automates the process of tremor types recognition. Finding the optimal model and its corresponding parameters is not a straightforward process. The resulting workflow, however, provides valuable information in understanding the interplay and impact of the different features and their parameters to the behavior and performance of the classifier system. The resulting model analysis helps identify the necessary locations for the placement of sEMG electrodes and relevant features that have significant impact in the process of classification. These information can help clinicians in streamlining the process of diagnosis without sacrificing its accuracy.

Kalman filtering of accelerometer and electromyography (EMG) data in pathological tremor sensing system

Currently there is a lack of objective clinical diagnosis and classification of tremor is difficult when it is subtle. Thus in previous work, a sensing system has been developed to quantify pathological tremor in human upper limb. In this paper, a Kalman filter algorithm to fuse information from accelerometers and surface electromyography is proposed. As the ground truth, an optical motion tracking system will be utilized. Then two sensor fusion algorithms based on Kalman filter are formulated to estimate the joint angle of the limb from the reading of accelerometers and surface EMG. Initial results using tremor data from two Parkinsons disease patients show promising future in this sensor fusion. The sensing system and the algorithms proposed are useful for actively compensating the tremor and helping the clinicians in tremor diagnostics.

Pointing with the wrist: a postural model for Donders' law

The central nervous system uses stereotypical combinations of the three wrist/forearm joint angles to point in a given (2D) direction in space. In this paper, we first confirm and analyze this Donders’ law for the wrist as well as the distributions of the joint angles. We find that the quadratic surfaces fitting the experimental wrist configurations during pointing tasks are characterized by a subject-specific Koenderink shape index and by a bias due to the prono-supination angle distribution. We then introduce a simple postural model using only four parameters to explain these characteristics in a pointing task. The model specifies the redundancy of the pointing task by determining the one-dimensional task-equivalent manifold (TEM), parameterized via wrist torsion. For every pointing direction, the torsion is obtained by the concurrent minimization of an extrinsic cost, which guarantees minimal angle rotations (similar to Listing’s law for eye movements) and of an intrinsic cost, which penalizes wrist configurations away from comfortable postures. This allows simulating the sequence of wrist orientations to point at eight peripheral targets, from a central one, passing through intermediate points. The simulation first shows that in contrast to eye movements, which can be predicted by only considering the extrinsic cost (i.e., Listing’s law), both costs are necessary to account for the wrist/forearm experimental data. Second, fitting the synthetic Donders’ law from the simulated task with a quadratic surface yields similar fitting errors compared to experimental data.

Online pathological tremor characterization using extended Kalman filtering

This paper describes different algorithms that perform online pathological tremor characterization in terms of acceleration. Two distinct parametricmodels are used, an Auto-Regressive (AR) model and an harmonic model. Both models are recursively estimated with Extended Kalman Filters (EKFs). Experimental data was obtained with low cost sensors and the results are compared in terms of spectrogram estimation and prediction performance.

An Extended Kalman filtering of accelerometer and surface electromyography data for attenuation of pathological tremor

Previously a Kalman filter has been developed to estimate joint angle of the tremulous upper limb using data from accelerometer (ACC) and surface electromyography (sEMG). Results have shown that the fused information can be useful for actively compensating the tremor and helping the clinicians in tremor diagnostics. In this paper, an improvement for the current algorithm is proposed by implementing Extended Kalman Filter (EKF). There is electromechanical delay between the muscle activation (sensed by sEMG) and onset of motion (sensed by ACC). Thus some information from the sEMG will be extracted first then it will be fed to the EKF algorithm together with the measurement from ACC.Weighted-Frequency Linear Combiner (WFLC) is used to extract the frequency of the sEMG data. The EKF will then be able to estimate the amplitude and phase of the tremor, along with the accelerometer bias. The extracted parameters of the tremor will be useful for its attenuation. The recursive nature of WFLC and EKF algorithm enables a real time implementation.

Analysis of Accuracy in Pointing with Redundant Hand-held Tools: A Geometric Approach to the Uncontrolled Manifold Method

This work introduces a coordinate-independent method to analyse movement variability of tasks performed with hand-held tools, such as a pen or a surgical scalpel. We extend the classical uncontrolled manifold (UCM) approach by exploiting the geometry of rigid body motions, used to describe tool configurations. In particular, we analyse variability during a static pointing task with a hand-held tool, where subjects are asked to keep the tool tip in steady contact with another object. In this case the tool is redundant with respect to the task, as subjects control position/orientation of the tool, i.e. 6 degrees-of-freedom (dof), to maintain the tool tip position (3dof) steady. To test the new method, subjects performed a pointing task with and without arm support. The additional dof introduced in the unsupported condition, injecting more variability into the system, represented a resource to minimise variability in the task space via coordinated motion. The results show that all of the seven subjects channeled more variability along directions not directly affecting the task (UCM), consistent with previous literature but now shown in a coordinate-independent way. Variability in the unsupported condition was only slightly larger at the endpoint but much larger in the UCM.

Using electromechanical delay for real-time anti-phase tremor attenuation system using Functional Electrical Stimulation

In this paper, we propose a novel anti-phase tremor compensation method using surface electromyography (SEMG) and accelerometer (ACC). The usefulness of the SEMG signal is that it precedes the generated joint movement by 20–100 ms (electromechanical delay, EMD). Hence by detecting the tremor in advance, there is enough time window to do the necessary computation and to actuate the antagonist muscle by Functional Electrical Stimulation (FES). This is also possible because the time taken for FES to actuate the muscle is significantly less than that of the neural signal, as detected by SEMG. Specifically, what is proposed in this paper is algorithm to an estimate the EMD and to determine when to start/stop the FES such that anti-phase tremor cancellation. Experimental result from one Essential Tremor patient show 57% reduction in tremor power as measured by the ACC.

Accuracy and repeatability of parameter estimation methods from ambulatory data for the wrist joint

In this paper, as a preliminary study, we show that accuracy and repeatability in ambulatory measurements of wrist joint are related to movement conditions which are going to be used in a calibration procedure. We chose two representative in-vivo, non-invasive calibration methods of the human upper limb, from those available in literature, to estimate joint parameters. Developing an analytical model of wrist joint we used sets of synthetic data each of which containing different number of samples, joint covariations and noise to estimate the repeatability and accuracy of the methods in estimation. Afterwards, we used our mechanical mock-up to examine single joint motions as well as the rotation of both joints (i.e. flexion-extension rotation and radial-ulnar deviation) on accuracy and repeatability by calculating the mean and standard deviation of the relative errors. Finally, we show that the accuracy of adapted method (its relative error was less than 7%) is better than the other method in estimating the joint parameters.

Placement of accelerometers in a hand-held active tremor compensation instrument for high angular sensing resolution

Angular sensing resolution provided by accelerometers in Micron, a physiological tremor compensation instrument, is determined by noise levels of accelerometer outputs and placement of the accelerometers. The angular sensing resolution can be increased by properly placing accelerometers in the instrument. In this paper, propositions for the placement of accelerometers to obtain the highest possible angular sensing resolution in micromanipulation tasks are shown. Following the propositions, new designs of accelerometer placements to sense 6 degree-of-freedom instrument motion with higher angular sensing resolution are proposed. Comparison of noise levels between the current accelerometer placement design and proposed designs are made. Angular acceleration noise is reduced by 75.42% comparing to that due to the current placement design.