TIE-Non-Invasive Monitoring of Implantable Batteries Using a Swept Frequency Ultrasonic Reflection Method 核心 · 已核验
doi:10.21227/1r5k-2746
"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."
- 落地页
- https://ieee-dataport.org/documents/tie-non-invasive-monitoring-implantable-batteries-using-swept-frequency-ultrasonic
- 许可证
- CC-BY-4.0 (判读置信:inferred)
- 国内可访问性
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国内直连:可达 (2026-07-11 检测)
代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。 - 设备类型
battery- PHM 任务
health_state_assessment
传感器
| sensor_type: ultrasonic_sensor |
运行工况
| condition_type: environment |
溯源(PROV,7 条)
| source_url: https://ieee-dataport.org/documents/tie-non-invasive-monitoring-implantable-batteries-using-swept-frequency-ultrasonicsource_citation: quarry_mining_pool datacite#10.21227/1r5k-2746retrieved_on: 2026-07-09asserted_by: automated_harvestnote: 反向挖掘 v3(KLS-018,词表圈选+全量人工复核):level=L0 score=0.2;候选区,晋升需人工核验 |
| about_field: equipment_typessource_citation: graphrag 抽取自论文 doi:10.21227/1r5k-2746(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: battery;候选区,晋升需人工核验(ADR-26) |
| about_field: operating_conditionssource_citation: graphrag 抽取自论文 doi:10.21227/1r5k-2746(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: environment;候选区,晋升需人工核验(ADR-26) |
| about_field: sensorssource_citation: graphrag 抽取自论文 doi:10.21227/1r5k-2746(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: ultrasonic_sensor;候选区,晋升需人工核验(ADR-26) |
| about_field: taskssource_citation: graphrag 抽取自论文 doi:10.21227/1r5k-2746(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: health_state_assessment;候选区,晋升需人工核验(ADR-26) |
| about_field: source_citation: 人工核验:zfbin(委托批准 2026-07-10)retrieved_on: 2026-07-10asserted_by: human_curatorconfidence_level: human_verifiednote: 晋升核心区。晋升批次 05:KLS-018 挖掘池卡,逐卡逐断言对照自述核验(evidence/KLS-016/08) |
| about_field: china_accessibilitysource_citation: KLS-009 链接健康扫描(lychee 双通道)retrieved_on: 2026-07-11asserted_by: automated_harvestnote: 定期刷新标注,仅覆盖本字段;历史结果以最新扫描为准 |