Yadav Dinesh, Garg Ramesh Kumar, Chhabra Deepak, Yadav Rajkumar, Kumar Ashwani, Shukla Pratyoosh
Department of Mechanical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana India.
Optimization and Mechatronics Laboratory, Department of Mechanical Engineering, University Institute of Engineering and Technology, Maharshi Dayanand University, Rohtak, Haryana India.
3 Biotech. 2020 Aug;10(8):351. doi: 10.1007/s13205-020-02342-x. Epub 2020 Jul 22.
The present work illustrates the promising intervention of smart diagnostics devices through artificial intelligence (AI) and mechanobiological approaches in health care practices. The artificial intelligence and mechanobiological approaches in diagnostics widen the scope for point of care techniques for the timely revealing of diseases by understanding the biomechanical properties of the tissue of interest. Smart diagnostic device senses the physical parameters due to change in mechanical, biological, and luidic properties of the cells and to control these changes, supply the necessary drugs immediately using AI techniques. The latest techniques like sweat diagnostics to measure the overall health, Photoplethysmography (PPG) for real-time monitoring of pulse waveform by capturing the reflected signal due to blood pulsation), Micro-electromechanical systems (MEMS) and Nano-electromechanical systems (NEMS) smart devices to detect disease at its early stage, lab-on-chip and organ-on-chip technologies, Ambulatory Circadian Monitoring device (ACM), a wrist-worn device for Parkinson's disease have been discussed. The recent and futuristic smart diagnostics tool/techniques like emotion recognition by applying machine learning algorithms, atomic force microscopy that measures the fibrinogen and erythrocytes binding force, smartphone-based retinal image analyser system, image-based computational modeling for various neurological disorders, cardiovascular diseases, tuberculosis, predicting and preventing of Zika virus, optimal drugs and doses for HIV using AI, etc. have been reviewed. The objective of this review is to examine smart diagnostics devices based on artificial intelligence and mechanobiological approaches, with their medical applications in healthcare. This review determines that smart diagnostics devices have potential applications in healthcare, but more research work will be essential for prospective accomplishments of this technology.
本研究展示了智能诊断设备通过人工智能(AI)和机械生物学方法在医疗保健实践中的前景广阔的干预作用。诊断中的人工智能和机械生物学方法通过了解感兴趣组织的生物力学特性,拓宽了即时护理技术的范围,以便及时发现疾病。智能诊断设备能够感知由于细胞的机械、生物和流体特性变化而产生的物理参数,并利用人工智能技术立即提供必要的药物来控制这些变化。文中还讨论了诸如用于测量整体健康状况的汗液诊断技术、通过捕获因血液脉动而反射的信号来实时监测脉搏波形的光电容积脉搏波描记法(PPG)、用于早期检测疾病的微机电系统(MEMS)和纳机电系统(NEMS)智能设备、芯片实验室和芯片器官技术、动态昼夜监测设备(ACM,一种用于帕金森病的腕戴式设备)。此外,还综述了近期和未来的智能诊断工具/技术,如应用机器学习算法进行情绪识别、测量纤维蛋白原和红细胞结合力的原子力显微镜、基于智能手机的视网膜图像分析仪系统、针对各种神经系统疾病、心血管疾病、结核病的基于图像的计算建模、寨卡病毒的预测和预防、利用人工智能确定艾滋病毒的最佳药物和剂量等。本综述的目的是研究基于人工智能和机械生物学方法的智能诊断设备及其在医疗保健中的医学应用。本综述确定智能诊断设备在医疗保健中有潜在应用,但要实现该技术的预期成果,还需要更多的研究工作。