SCH: INT: Wearable knee Joint Health Sensing Using Acoustical Emissions

SCH：INT：使用声发射的可穿戴膝关节健康传感

• 批准号: 9981531
• 负责人: Omer Tolga Inan
• 金额: $ 5.01万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-27 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9981531
• 关键词: Accelerometer; Acoustics; Acute; Affect; Algorithms; American; Anterior Cruciate Ligament; Biological Markers; Cadaver; Clinic; Diagnosis; Evaluation; Feedback; Health; Health Status; Hospitals; Injury; Instruction; Joints; Knee; Knee Injuries; Knee joint; Lead; Measurement; Measures; Meniscus structure of joint; Modeling; Noise; Operative Surgical Procedures; Pain; Patients; Physical therapy; Population; Quality of life; Rehabilitation therapy; Risk; Signal Transduction; Skin; Sprain; Surface; Symptoms; Technology; Visit; base; clinically relevant; design; exercise rehabilitation; follow-up; programs; sensor; sound; tool

Every year, millions of Americans present at the hospital with knee injuries, such as meniscus tears or anterior cruciate ligament (AGL) sprains. Moreover, knee injuries are one of the most common causes of missed workdays. The current paradigm of treating knee injuries initially involves frequent physical therapy visits, subjective evaluations by experts, and possibly surgery; following these initial steps the patient continues to participate in physical therapy, periodically - and typically infrequently - returns to the clinic for follow-up subjective evaluations, and bases his I her joint health rehabilitation status mainly on symptoms and pain. There is no technology available currently to provide patients with knee injuries frequent, objective, and in-depth information regarding the status of their joint rehabilitation. The hypothesis for this project is that the sounds of the joints measured using sensors embedded in a wearable wrap can provide a clinically-relevant biomarker for joint health rehabilitation assessment, and can ultimately allow patients to tune their rehabilitation exercises dynamically based on objective feedback. This could potentially accelerate rehabilitation, reduce the risk of re-injury, and empower patients to be in control of their rehabilitation. This project proposes to study these sounds, and their measurement, with an integrative program including the following specific aims: (1) Design and implement an ultra-low noise, high-bandwidth, wafer-level-packaged micro-accelerometer chip for contact measurement of joint sounds from the skin surface with high fidelity; (2) Elucidate the origin of the sounds and how they change with injury using a cadaver model; (3) Develop algorithms for extracting salient features from the joint sound signals that can be used to assess joint health; (4) Evaluate the sensors and analytics in a population of 20 subjects with meniscus tears, before and after surgery, and twice during rehabilitation several months following surgery. RELEVANCE (See Instructions): Knee injuries affect millions of Americans lead to missed workdays as well as reducing the quality of life. Currently, after an acute knee injury is diagnosed, there are very few tools available during rehabilitation to provide feedback to patients regarding any improvements or setbacks to their knee health status.

每年，数以百万计的美国人因半月板等膝盖受伤而来到医院 撕裂或前交叉韧带(AGL)扭伤。此外，膝盖受伤是最严重的 错过工作日的常见原因。当前膝部损伤初期治疗的范例 包括频繁的物理治疗，专家的主观评估，可能还有手术； 在这些最初的步骤之后，患者继续定期参加物理治疗- 而且通常不经常返回诊所进行后续的主观评估，并根据他的 她的关节健康康复状况主要以症状和疼痛为主。没有一种技术 目前可为膝关节损伤患者提供频繁、客观、深入的 关于他们联合康复情况的信息。这个项目的假设是 使用嵌入在可穿戴保护套中的传感器测量关节的声音可以提供 临床相关的生物标志物，用于联合健康康复评估，并最终可以 患者根据客观反馈动态调整他们的康复练习。这可能会 有可能加速康复，降低再次受伤的风险，并使患者能够 控制他们的康复。这个项目计划研究这些声音，以及它们的 测量，包括以下具体目标的综合方案：(1)设计和 实现超低噪声、高带宽、晶圆级封装的微加速度计芯片 用于从皮肤表面高保真地测量关节声音；(2)阐明 使用身体模型研究声音的来源及其随损伤的变化；(3)发展 用于从联合声音信号中提取显著特征的算法 关节健康；(4)评估20名半月板受试者的传感器和分析方法 手术前后的泪水，以及术后几个月康复期间的两次泪水。 相关性(请参阅说明)： 膝盖受伤影响了数百万美国人，导致错过工作日，降低质量 生活的一部分。目前，在诊断出急性膝部损伤后，在 康复向患者提供关于他们的任何改善或挫折的反馈 膝盖健康状况。