During the preceding decades, human gait analysis has been the center of attention for the scientific community, while the association between gait analysis and overall health monitoring has been extensively reported. Technological advances further assisted in this alignment, resulting in access to inexpensive and remote healthcare services. Various assessment tools, such as software platforms and mobile applications, have been proposed by the scientific community and the market that employ sensors to monitor human gait for various purposes ranging from biomechanics to the progression of functional recovery. The framework presented herein offers a valuable digital biomarker for diagnosing and monitoring Parkinson's disease that can help clinical experts in the decision-making process leading to corrective planning or patient-specific treatment. More accurate and reliable decisions can be provided through a wide variety of integrated Artificial Intelligence algorithms and straightforward visualization techniques, including, but not limited to, heatmaps and bar plots. The framework consists of three core components: the insole pair, the mobile application, and the cloud-based platform. The insole pair deploys 16 plantar pressure sensors, an accelerometer, and a gyroscope to acquire gait data. The mobile application formulates the data for the cloud platform, which orchestrates the component interaction through the web application. Utilizing open communication protocols enables the straightforward replacement of one of the core components with a relative one (e.g., a different model of insoles), transparently from the end user, without affecting the overall architecture, resulting in a framework with the flexibility to adjust its modularity.
翻译:在过去几十年中,人类行踪分析一直是科学界关注的中心,而轨迹分析与总体健康监测之间的联系也得到了广泛报道。技术进步进一步协助了这一协调,从而导致获得廉价和偏远的保健服务。科学界和市场提出了各种评估工具,如软件平台和移动应用,利用传感器监测人类行踪,从生物机能到功能恢复的进展等各种目的。本文提出的框架为诊断和监测帕金森病提供了宝贵的数字生物标志,有助于临床专家在导致纠正规划或针对病人治疗的决策过程中取得临床专家。可以通过多种综合人工智能算法和直观直观的直观技术提供更准确和可靠的决定,包括但不限于热图和条形图。框架由三个核心组成部分组成:骨质配对、移动应用和云基平台模型。内衣配有16个计划压力传感器、加速度计和透析仪,可以帮助临床专家做出更准确和可靠的决定,通过广泛的综合人工智能算法和直观化技术,包括(但不限于热图和条形图 ) 将一个移动应用软件设计成一个清晰的模型,从而获得一个直接的版本。通过一个用户操作平台,将数据转换成一个清晰的系统。