Tamara Supuk

Design, Development and Testing of a Low-Cost sEMG System and Its Use in Recording Muscle Activity in Human Gait

Surface electromyography (sEMG) is an important measurement technique used in biomechanical, rehabilitation and sport environments. In this article the design, development and testing of a low-cost wearable sEMG system are described. The hardware architecture consists of a two-cascade small-sized bioamplifier with a total gain of 2,000 and band-pass of 3 to 500 Hz. The sampling frequency of the system is 1,000 Hz. Since real measured EMG signals are usually corrupted by various types of noises (motion artifacts, white noise and electromagnetic noise present at 50 Hz and higher harmonics), we have tested several denoising techniques, both on artificial and measured EMG signals. Results showed that a wavelet—based technique implementing Daubechies5 wavelet and soft sqtwolog thresholding is the most appropriate for EMG signals denoising. To test the system performance, EMG activities of six dominant muscles of ten healthy subjects during gait were measured (gluteus maximus, biceps femoris, sartorius, rectus femoris, tibialis anterior and medial gastrocnemius). The obtained EMG envelopes presented against the duration of gait cycle were compared favourably with the EMG data available in the literature, suggesting that the proposed system is suitable for a wide range of applications in biomechanics.

Assessment of reach-to-grasp trajectories toward stationary objects

BACKGROUND Patients with pronounced spasticity reveal difficulties in hand opening during the approaching grasping phase. The general description and assessment procedures of reach-to-grasp movement for rehabilitation purposes is still not established. There is a necessity to develop a universal methodology to describe the approaching phase in grasping which would allow clinical evaluation of movement pathologies. METHODS In the paper, the evaluation of approaching trajectories assessed during grasping by healthy subjects is described. The experiment, undertaken by 7 healthy volunteers, consisted of grasping three different stationary objects positioned in various poses by a robot. 3D recordings of the hand and fingertip trajectories were performed. The kinematic trajectories of the hand and finger markers were analysed in order to evaluate the reach-to-grasp movement. FINDINGS The results of the kinematic analysis suggest that the reach-to-grasp movement of a healthy subject can be divided into 3 dominant phases (hand acceleration, hand deceleration, and final closure of the fingers). INTERPRETATION The presented evaluation method can provide relevant information on the modalities the hand preshapes and approaches toward the object in order to obtain a stable grasp. The potential use of the approach for rehabilitation purposes is discussed.

New Kinematic Parameters for Quantifying Irregularities in the Human and Humanoid Robot Gait

Gait patterns of humans and humanoid robots are often described by analysing changes in angular rotation of hip, knee and ankle joints during one gait cycle. Each joint displays specific behaviour and irregularities of the gait pattern could be detected by measuring displacements from the normal rotation curve, while small deviations of individual gait characteristics are usually not easily detected. In this paper, an advanced gait analysis method is proposed, which incorporates analysis of angular data and its derivations of hip, knee, and ankle joints, presented in the phase plane. The gait kinematics was measured using a system based on active markers and fast digital cameras. The experiment included measurements on thirty healthy, barefoot humans while walking on a treadmill. We also simulated types of irregular gait, by measurements on subjects wearing knee constraints. The new kinematic parameters which are introduced clearly indicated the discrepancy between normal, healthy gait trials and irregular gait trials. The proposed gait factor parameter is a valuable measure for the detection of irregularities in gait patterns of humans and humanoid robots.

Estimation of hand preshaping during human grasping by using instrumented glove

This paper deals with the novel method for evaluating hand preshaping during reaching-to-grasp movement. The method makes use of all five fingers in estimation of prehension [1]. The investigation was performed on six healthy subjects grasping three different objects at various positions and orientations. The objects were presented to the subjects by means of a robot, which also induced perturbations in both object position and orientation. Positions of markers attached to the finger-tips and dorsum of the hand were recorded by means of a 3D optical tracking system, Optotrak. In the data analysis the adjacent finger-tips were interconnected, thus obtaining a planar pentagon whose various characteristics were investigated and discussed. New parameters for the evaluation of finger preshaping, such as pentagon surface area, angle between the pentagon and hand normal vectors, and the angle between the pentagon and object normal vectors between were introduced, [1]. We have also investigated the hand orientation during prehensile movements by analysing the angle between the vectors emanating from the palm and object to be grasped [2]. As the next step of improving the applicability of the method is the implementation of the instrumented glove. 3D optical motion tracking system is reliable, but robust and complicate to use, especially in the rehabilitation environment. On the other hand, the instrumented glove is easy to use, and, as we shoved, provides reliable data. We performed simultaneous measurement of prehensile movement by glove and Optotrak. We used biomechanical model of the hand to calculate the positions of the fingertips on the basis of the fingers joint angles measured by the glove. The data calculated from the glove outputs were compared with the markers positions recorded by Optotrak. So obtained data were used to calculate hand opening described by pentagon square area. The proposed pentagon approach is expected to be useful in future work when examining grasping abilities of subjects with neuromuscular disorders.