"TIE-Non-Invasive Monitoring of Implantable Batteries Using a Swept Frequency Ultrasonic Reflection Method"

"Accurate estimation of the state of charge (SOC) and state of health (SOH) is vital for implantable batteries to ensure patient safety, prolong device lifespan, and minimize the need for surgical interventions. Ultrasonic sensing offers unique benefits in such applications, including non-invasiveness, no extra power consumption for sensing units, and low integration complexity. However, existing ultrasonic approaches often rely on feature extraction at a dominant frequency via short-time pulse excitation, making their performance sensitive to the dominant frequency selected. Deviations in dominant frequency selection can introduce inconsistencies in SOC and SOH estimation. Moreover, simultaneous estimation of SOC and SOH typically requires continuous monitoring over extended periods. To overcome these limitations, this paper proposes a swept frequency ultrasonic reflection (SFUR) method. Unlike conventional approaches that rely on single-frequency analysis, SFUR employs swept-sine excitation to capture multi-frequency response features, thereby eliminating dependency on dominant frequency selection. Under static physiological conditions, using only one sweep, the method is capable of extracting a dual feature set comprising the amplitude and phase of the reflected signal across multiple frequencies to estimate both SOC and SOH effectively and without continuous monitoring over extended periods. Under physiological variability conditions, such as skin tissue thickness variations, a gene-encoded classifier is introduced to achieve good SOC estimation accuracy. Experimental results validate the effectiveness and advantages of the proposed method for non-invasive monitoring of implantable batteries."