Abstract

Spinal deformation due to scoliosis affects millions of people globally. It is majorly affecting growing children or occurs during adolescence. With its unpredictable cause of the occurrence, the cure is still unidentified. The best approach for physicians to provide care for these patients is through the prevention of curve progression. To be able to achieve that, physicians conduct multiple tests and examinations to make a treatment plan for the patient. A decision developed based on patient data is of great significance for the prognosis of scoliosis. However, the existing system relies on multiple analog scales that require manual entry of patient data on patient files which fails to show the trend of the patient’s condition. Our IoT-enabled prototype introduces digital assessment in the field of scoliosis and other complex spine disorders. It aims to simplify the diagnosis and monitoring of scoliosis by reducing human error and misdiagnosis due to inefficient and insensitive existing tools the physicians have to rely on. It comes with a digital LCD, 3in1 modes at one click gives high accuracy measurement that physician is looking for. It’s a wireless device that communicates with the physician’s workstation and enables the transmission of data from the device to the workstation, reducing the workload of the physicians by updating the patient record automatically. It’s a point-of-care device that can be operated in any location including patients in remote locations as well. Early and accurate diagnosis is crucial to avoid spine surgery costing between $60k to $100k and have a spine free of rods.

Problem

Idiopathic scoliosis is a complex spine distortion that affects millions of people around the world. Scoliosis prognosis depends largely on data-driven methods from various examinations that are independent of each other. All the current practice relies on manual assessment approaches, that are prone to human errors i.e., subjected to physician experiences, inter and intra-observer variability, and reading parallax in using the scoliometer. Also, a few of the methods mentioned above require further mathematical calculation to transform the imperial unit reading into an SI unit. The current state of art techniques includes manual measurement with the hand-written patient record. The physicians conduct various tests and examinations to provide a prognosis. However different physicians use different tests, which results in a pool of unstructured and incomplete handwritten data, failing to show the trend or pattern of the patient’s condition over time. This manual practice of data storage and retrieval is a tedious process, and the trend of patients’ progressive monitoring measurement is hardly observed and analyzed accurately. Data sharing between physicians in the same institution are also not as straightforward if compared to the proposed digital data repository.

Solution

This project was started in consultation with a group of orthopedic surgeons from the University Malaya Medical Centre and the problem statement has been validated by a market survey done with multiple medical practitioners from different medical facilities. Among our interviewees were orthopedic surgeons, physiotherapists, and chiropractors from different hospitals and centers. The majority of the interviewees agreed upon having a digital scale would ease their problem of irregularities with analog scales. They were thrilled with having a multi-functional digital scale that can measure various asymmetries of the body with a few clicks of buttons. The majority of the practitioners have agreed that a lot of tests and examinations need to be performed to assess the scoliosis condition. The more structured patient data they have, the better and faster the prognosis is made. Structured digitized data enables them to see the trend of patient conditions and also helps in making assumptions about patients’ conditions in the future. However, with different practitioners using different methods and tools to monitor, patient data becomes a vast pool of raw data points that is difficult to be utilized to its maximum potential. Having a system that can automatically store various data points could help the practitioners in reducing workload and easy collaboration with other experts.

Keeping various aspects into consideration this invention is built into a device that can quantitatively diagnose and monitor scoliosis. The device then transmits the data to the workstation where it is analyzed and stored. The data analysis would evaluate the current data with the previous data and display multiple trends of the patient’s condition over time. This strategy would help the physician to understand each patient better based on their data trend. Hence, they will be able to give better attention to patients whose condition is deteriorating at a faster rate.

Working Principle

The device uses multiple sensors and a microprocessor to gather the quantitative value of patients’ asymmetries. It is able to measure shoulder difference, angle of trunk rotation, and hump height difference. These are key indicators to monitor the patient’s physical condition. The device uses acromion as the reference point to compare the left and right shoulders difference. It is moved along the spine to measure the angle of trunk rotation and the two prominent humps on the patient’s back are utilized to measure the hump height difference. With the help of the Wi-Fi module installed in the device, it sends the data to the physician’s workstation where the current data is analyzed with the previously stored data, and trends are generated to display the patient’s progress over time.

This is a first of its kind in the market and has already been patented at MyIPO Malaysia (Intellectual Property Corporation of Malaysia). The uniqueness of this device is that it is an automated digital device that offers 3in1 measurements with just a click of a few buttons. It straight away displays the result physicians are looking for without them having to do any other manual calculations. No more manual measurement and error during recording. It gives faster results hence minimizing discomfort for the patients during physical examinations. Its higher sensitivity and accuracy could reduce physicians’ dependence on X-rays. This prototype had undergone two cycles of clinical trial with 32 scoliosis patients at University Malaya Medical Centre (UMMC), Orthopaedic Surgery Department. The parameters were measured using the conventional tools available in UMMC which include the Baseline® scoliosis meter and Scoliometer. The clinical testing had been conducted on 32 patients and the results obtained from our invention and conventional tools were recorded and tabulated. Based on the clinical trial finding, our invention is able to produce an accurate clinical index against the existing gold standard, with shorter measurement durations and higher diagnosis efficiency.