Control of Functional Electrical Stimulation Systems Using Simultaneous Pulse Width, Amplitude, and Frequency Modulations.

BACKGROUND: One significant challenge of developing a controller for functional electrical stimulation systems is the time-variant nonlinear dynamics of the neuromusculoskeletal system. In the conventional methods, the stimulation intensity is adjusted by a controller; however, the stimulation frequency is always constant. The previous studies have shown that the stimulation frequency is effective in fatigue formation. OBJECTIVES: A simultaneous modulation of the stimulation intensity and frequency is proposed to improve the joint controllability and muscle endurance. The presented control method determines pulse width (PW), amplitude, and frequency of the electrical stimulation signal, synchronously. Three different modulations are applied for control of the knee joint to show the superiority of the proposed modulation. METHODS: The stimulation intensity is controlled by the PW and pulse amplitude of the electrical signal using an adaptive fuzzy terminal sliding mode controller and a fuzzy logic controller, respectively. Also, a fuzzy logic controller is applied to adjust the stimulation frequency. The proposed method is utilized to control the knee joint movement using quadriceps femoris muscles for ten paraplegic subjects. RESULTS: Two different test protocols are defined to evaluate the presented method: A protocol for testing the controllability and another protocol for evaluating the produced muscle endurance. The average value of the root mean square of the tracking error was 6.4° for the proposed method which is 5.1° and 9.6° less than PW modulation and synchronous PW and amplitude modulation, respectively. The average time duration of the knee full extension was 96 sec for the proposed method which is 17 and 26 sec more than PW modulation and synchronous PW and amplitude modulation, respectively. CONCLUSIONS: The experimental results show that control performance and tracking ability of the joint reference trajectory are improved by using the simultaneous modulation of PW, amplitude, and frequency.

Finite-Set Model Predictive Control of Melanoma Cancer Treatment Using Signaling Pathway Inhibitor of Cancer Stem Cell.

Drug delivery is one of the most important issues in the treatment of cancer and surviving the patient. Recently, with a combination of mathematical models of the tumor growth and control theory, optimal drug delivery can be planned, individually. The goal is reducing the tumor volume with minimum side effects on the patient. One of the most important challenges of the modeling is considering the drug resistance, which may lead to failure of the treatment. In this paper, a mathematical model is proposed for describing the growth dynamics of the melanoma tumor cells. It is assumed that the melanoma cancer is treated with Notch signaling pathway inhibitors of the cancer stem cells. The model parameters are identified based on experimental data obtained from 13 male nude mice with an induced melanoma cancer involved in a dual antiplatelet therapy (DAPT) program. The mathematical model is used to determine if DAPT can reduce the growth rate of the tumor. Then an optimal drug delivery plan for the treatment of every animal model is presented, individually using finite-set model predictive control method. The results show that the proposed model can estimate the drug's effect on the treatment of melanoma cancer.

Long-Term Inhibition of Notch in A-375 Melanoma Cells Enhances Tumor Growth Through the Enhancement of AXIN1, CSNK2A3, and CEBPA2 as Intermediate Genes in Wnt and Notch Pathways.

Notch suppression by gamma-secretase inhibitors is a valid approach against melanoma. However, most of studies have evaluated the short-term effect of DAPT on tumor cells or even cancer stem cells. In the present study, we surveyed the short-term and long-term effects of DAPT on the stem cell properties of A375 and NA8 as melanoma cell lines. The effects of DAPT were tested both in vitro and in vivo using xenograft models. In A375 with B-raf mutation, DAPT decreased the level of NOTCH1, NOTH2, and HES1 as downstream genes of the Notch pathway. This was accompanied by enhanced apoptosis after 24 h treatment, arrest in the G2-M phase, and impaired ability of colony and melanosphere formation at the short term. Moreover, tumor growth also reduced during 13 days of treatment. However, long-term treatment of DAPT promoted tumor growth in the xenograft model and enhanced the number and size of colonies and spheroids in vitro. The gene expression studies confirmed the up-regulation of Wnt and Notch downstream genes as well as AXIN1, CSNK2A3, and CEBPA2 following the removal of Notch inhibitor in vitro and in the xenograft model. Moreover, the Gompertz-based mathematical model determined a new drug resistance term in the present study. Our data supported that the long-term and not short-term inhibition of Notch by DAPT may enhance tumor growth and motility through up-regulation of AXIN1, CSNK2A3, and CEBPA2 genes in B-raf mutated A375 cells.

Dynamic optimization of walker-assisted FES-activated paraplegic walking: simulation and experimental studies.

In this paper, we propose a musculoskeletal model of walker-assisted FES-activated paraplegic walking for the generation of muscle stimulation patterns and characterization of the causal relationships between muscle excitations, multi-joint movement, and handle reaction force (HRF). The model consists of the lower extremities, trunk, hands, and a walker. The simulation of walking is performed using particle swarm optimization to minimize the tracking errors from the desired trajectories for the lower extremity joints, to reduce the stimulations of the muscle groups acting around the hip, knee, and ankle joints, and to minimize the HRF. The results of the simulation studies using data recorded from healthy subjects performing walker-assisted walking indicate that the model-generated muscle stimulation patterns are in agreement with the EMG patterns that have been reported in the literature. The experimental results on two paraplegic subjects demonstrate that the proposed methodology can improve walking performance, reduce HRF, and increase walking speed when compared to the conventional FES-activated paraplegic walking.

A decentralized modular control framework for robust control of FES-activated walker-assisted paraplegic walking using terminal sliding mode and fuzzy logic control.

A major challenge to developing functional electrical stimulation (FES) systems for paraplegic walking and widespread acceptance of these systems is the design of a robust control strategy that provides satisfactory tracking performance. The systems need to be robust against time-varying properties of neuromusculoskeletal dynamics, day-to-day variations, subject-to-subject variations, external disturbances, and must be easily applied without requiring offline identification during different experimental sessions. Another major problem related to walker-assisted FES-activated walking concerns the high metabolic rate and upper body effort that limit the clinical applications of FES systems. In this paper, we present a novel decentralized modular control framework for robust control of walker-assisted FES-activated walking. For each muscle-joint dynamics, an independent module control is designed, and the dynamics of the plant are identified online. This process requires no prior knowledge about the dynamics of the plant to be controlled and no offline learning phase. The module is based on adaptive fuzzy terminal sliding mode control and fuzzy logic control. The module control adjusts both pulse-amplitude and pulsewidth of the stimulation signal in such a way that upper body effort is minimized and the lower extremity walking pattern lies within a defined boundary of the reference trajectory. The proposed control strategy has been evaluated on three paraplegic subjects. The results showed that accurate tracking performance and smooth walking pattern were achieved. This favorable performance was obtained without requiring offline identification, manual adjustments, and predefined ON/OFF timing of the muscles.

Adaptive terminal sliding mode control of ankle movement using functional electrical stimulation of agonist-antagonist muscles.

This paper presents a robust control strategy which is based on synergistic combination of an adaptive controller with terminal sliding mode control (TSMC) for online control of ankle movement using functional electrical stimulation (FES) of dorsiflexor and plantar flexor muscles in paraplegic subjects. The major advantage of TSMC derives from the property of robustness to system uncertainties and external disturbances with fast convergence without imposing strong control force. To implement TSMC, a model of neuromusculoskeletal system should be presented in standard canonical form. In this work, we design an adaptive updating law to estimate the parameters of the model during online control without requiring offline learning phase. The experimental results on two paraplegic subjects show that the TSMC provides excellent tracking control for different reference trajectories and could generate control signals to compensate the effects of muscle fatigue and external disturbance.