Department of Electrical Engineering, Indian Institute of Technology (IIT) Hyderabad, Kandi 502285, India.
School of Electronics Engineering, VIT-AP University, Amaravati 522237, India.
Sensors (Basel). 2022 Feb 23;22(5):1756. doi: 10.3390/s22051756.
Functional electrical stimulation (FES) is a safe, effective, and general approach for treating various neurological disorders. However, in the case of FES usage for implantable applications, charge balancing is a significant challenge due to variations in the fabrication process and electrode tissue interface (ETI) impedance. In general, an active charge balancing approach is being used for this purpose, which has limitations of additional power consumption for residual voltage calibration and undesired neurological responses. To overcome these limitations, this paper presents a reconfigurable calibration circuit to address both ETI variations and charge balancing issues. This reconfigurable calibration circuit works in two modes: An impedance measurement mode (IMM) for treating ETI variations and a hybrid charge balancing mode (HCBM) for handling charge balance issues. The IMM predicts the desired stimulation currents by measuring the ETI. The HCBM is a hybrid combination of electrode shorting, offset regulation, and pulse modulation that takes the best features of each of these techniques and applies them in appropriate situations. From the results, it is proved that the proposed IMM configuration and HCBM configuration have an optimal power consumption of less than 44 μW with a power ratio ranging from 1.74 to 5.5 percent when compared to conventional approaches.
功能性电刺激（FES）是一种安全、有效且通用的治疗各种神经紊乱的方法。然而，在 FES 用于植入式应用的情况下，由于制造工艺和电极-组织界面（ETI）阻抗的变化，电荷平衡是一个重大挑战。通常，为此目的使用主动电荷平衡方法，但存在由于残余电压校准和不期望的神经响应而导致的额外功耗的限制。为了克服这些限制，本文提出了一种可重构校准电路来解决 ETI 变化和电荷平衡问题。该可重构校准电路有两种工作模式：用于处理 ETI 变化的阻抗测量模式（IMM）和用于处理电荷平衡问题的混合电荷平衡模式（HCBM）。IMM 通过测量 ETI 来预测所需的刺激电流。HCBM 是电极短路、偏移调节和脉冲调制的混合组合，它采用了这些技术的最佳特点，并在适当的情况下应用它们。结果表明，与传统方法相比，所提出的 IMM 配置和 HCBM 配置具有小于 44μW 的最佳功耗，功率比范围为 1.74 至 5.5%。
