A novel method for in-situ extracting bio-impedance model parameters optimized for embedded hardware.

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R∞, R1 and C are estimated using the derived set of equations based on measured values of real (R) and imaginary part (X) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R/X with respect to angular frequency. The optimal value for parameter α is estimated using a brute force method. The estimation accuracy of the proposed method is very similar with the relevant work from the existing literature. Moreover, performance evaluation was performed using the MATLAB software installed on a laptop, as well as on the three embedded-hardware platforms (Arduino Mega2560, Raspberry Pi Pico and XIAO SAMD21). Obtained results showed that the used platforms can perform reliable bioimpedance processing with the same accuracy, while Raspberry Pi Pico is the fastest solution with the smallest energy consumption.

A new digital resonant current controller for AC power converters based on the advanced Z-transform.

In this paper, we present a new digital resonant current controller that can be applied in single-phase and three-phase alternating current (AC) power converters, based on voltage source inverters (VSI) with pulse width modulation (PWM). Since power converters based on PWM introduce fractional time delays regarding the sampling period (Ts), because of the current sampling and PWM command updating techniques that are employed, there is a need to develop analytical tools for precise modelling of these types of delays. To achieve this, the advanced Z-transform is applied in order to model the AC controllers in VSIs with PWM for the general case of a fractional time delay, including power converters with current sampling within a PWM period at any chosen time instance. This new approach to power converter modelling and current sampling allowed us to develop a modified resonant AC current controller for a VSI with RL load, based on the pole-placement parameter tuning method. It includes fractional time delays, which are conventionally employed in the power converter design, in the controller parameter derivations, and introduces the minimal order resonant controller that enables strict placement of all closed-loop control system poles. Simulations and experimental tests are carried out to show the improvements introduced by novel solution in this paper compared with conventional resonant current controllers. In the analysis of dynamic performance and robustness, in this paper conventional indices are applied to compare the proposed controller with a conventional design.

Cascade Control of Antagonistic VSA-An Engineering Control Approach to a Bioinspired Robot Actuator.

A cascade control structure for the simultaneous position and stiffness control of antagonistic tendon-driven variable stiffness actuators (VSAs) implemented in a laboratory setup is presented in the paper. Cascade control has the ability to accelerate, additionally stabilize, and reduce oscillations, which are all extremely important in systems such as a tendon-driven compliant actuators with elastic transmission. Inner-loop controllers are closed in terms of motor positions, and outer-loop controllers in terms of actuator position and estimated stiffness. The dominant dynamics of the system (position and stiffness), composed of the mechanical part and inner loops, are identified by a closed-loop auto-regressive with exogenous input (ARX) model. The outer-loop controllers are tuned on the basis of experimentally identified transfer functions of the system in several nominal operating points for different stiffness values. After the system is identified, a controller bank is generated in which a pair of actuator position and stiffness controllers correspond to a nominal operating point and covers the area surrounding the nominal point for which it is designed. The controllers used are integral-proportional differential (I-PD) and integral-proportional (I-P) controllers, which are a variation of the PID and PI controllers with dislocated proportional and derivative gains from a direct to feedback branch that result to no overshoot for even fast reference changes (i.e., step signal), which is essential for preventing tendon slackening (meeting the pulling constraint). Analytical formulas for controller tuning based on only one parameter, λ, are also presented. Since position and stiffness loops are decoupled, it is possible to change λ for both loops independently and adjust their performance separately according to the needs. Also, the controller structure secures the smooth response without overshooting step reference or step disturbance signal, which make practical implementation possible. After all the controllers were designed, the cascade control structure for simultaneous position and stiffness control was successfully evaluated in a laboratory setup. Thus, the presented control approach is simple to implement, but with a performance that ensures a pulling constraint for tendon-driven actuators as a foundation for bioinspired antagonistic VSAs.

ECG artifact cancellation in surface EMG signals by fractional order calculus application.

BACKGROUND AND OBJECTIVE: New aspects for automatic electrocardiography artifact removal from surface electromyography signals by application of fractional order calculus in combination with linear and nonlinear moving window filters are explored. Surface electromyography recordings of skeletal trunk muscles are commonly contaminated with spike shaped artifacts. This artifact originates from electrical heart activity, recorded by electrocardiography, commonly present in the surface electromyography signals recorded in heart proximity. For appropriate assessment of neuromuscular changes by means of surface electromyography, application of a proper filtering technique of electrocardiography artifact is crucial. METHODS: A novel method for automatic artifact cancellation in surface electromyography signals by applying fractional order calculus and nonlinear median filter is introduced. The proposed method is compared with the linear moving average filter, with and without prior application of fractional order calculus. 3D graphs for assessment of window lengths of the filters, crest factors, root mean square differences, and fractional calculus orders (called WFC and WRC graphs) have been introduced. For an appropriate quantitative filtering evaluation, the synthetic electrocardiography signal and analogous semi-synthetic dataset have been generated. The examples of noise removal in 10 able-bodied subjects and in one patient with muscle dystrophy are presented for qualitative analysis. RESULTS: The crest factors, correlation coefficients, and root mean square differences of the recorded and semi-synthetic electromyography datasets showed that the most successful method was the median filter in combination with fractional order calculus of the order 0.9. Statistically more significant (p < 0.001) ECG peak reduction was obtained by the median filter application compared to the moving average filter in the cases of low level amplitude of muscle contraction compared to ECG spikes. CONCLUSIONS: The presented results suggest that the novel method combining a median filter and fractional order calculus can be used for automatic filtering of electrocardiography artifacts in the surface electromyography signal envelopes recorded in trunk muscles.

Dominant pole placement with fractional order PID controllers: D-decomposition approach.

Dominant pole placement is a useful technique designed to deal with the problem of controlling a high order or time-delay systems with low order controller such as the PID controller. This paper tries to solve this problem by using D-decomposition method. Straightforward analytic procedure makes this method extremely powerful and easy to apply. This technique is applicable to a wide range of transfer functions: with or without time-delay, rational and non-rational ones, and those describing distributed parameter systems. In order to control as many different processes as possible, a fractional order PID controller is introduced, as a generalization of classical PID controller. As a consequence, it provides additional parameters for better adjusting system performances. The design method presented in this paper tunes the parameters of PID and fractional PID controller in order to obtain good load disturbance response with a constraint on the maximum sensitivity and sensitivity to noise measurement. Good set point response is also one of the design goals of this technique. Numerous examples taken from the process industry are given, and D-decomposition approach is compared with other PID optimization methods to show its effectiveness.

A fast closed-loop process dynamics characterization.

Stable, integrating and unstable processes, including dead-time, are analyzed in the loop with a known PI/PID controller. The ultimate gain and frequency of an unknown process G(p)(s), and the angle of tangent to the Nyquist curve G(p)(iω) at the ultimate frequency, are determined from the estimated Laplace transform of the set-point step response of amplitude r0. Gain G(p)(0) is determined from the measurements of the control variable and known r0. These estimates define a control relevant model G(m)(s), making possible the use of the previously determined and memorized look-up tables to obtain PID controller guaranteeing desired maximum sensitivity and desired sensitivity to measurement noise. Simulation and experimental results, from a laboratory thermal plant, are used to demonstrate the effectiveness and merits of the proposed method.

Adaptive band-pass filter (ABPF) for tremor extraction from inertial sensor data.

Cancelling pathological tremor in everyday living activities may be possible with functional electrical stimulation (FES). One such feasible FES system with feedback from inertial sensors would rely on tremor estimates in real time. We present an adaptive band-pass filter (ABPF) that estimates tremor from volitional hand movement with zero-phase lag. The proposed algorithm is simple and easy to implement. Performance of the ABPF is compared to one popular well-established method for tremor extraction (weighted-frequency Fourier linear combiner, WFLC) using both synthetic data and data from inertial sensors, recorded in tremor patients during "finger to nose" task execution. The results were comparable, favoring ability of ABPF for faster adaptation, higher accuracy and robustness.