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NIX delivered a cloud-based telehealth solution with AI analytics and a user-friendly interface, enabling early detection, better treatment, and remote monitoring for patients and physicians.
Healthcare
AI, Mobile Development, Web Development, Cloud Services, Internet of Things
Kotlin, Swift, Azure, .NET
Our client is a global provider of software products for the healthcare industry, committed to developing a solution that enhances the treatment efficiency of various musculoskeletal (MSK) conditions by creating a telehealth platform for remote monitoring of orthopedic patients. Using this solution, physicians monitor a patient’s state in real-time, remotely, with special IoT devices connected and controlled via a mobile app. Through these devices, the system collects biometric telemetry and transmits these data into the cloud. A special AI algorithm trained on the gait analysis dataset processes and evaluates received data and assists physicians in patient condition assessment and optimizing treatment plans.
The client faced difficulties finding a software engineering company, considering that their ideal candidate had to have in-depth expertise in creating AI and IoT solutions, and be familiar with all healthcare peculiarities. On the advice of their partners, the client contacted NIX United, and it was a perfect match. We have extensive experience creating IoT ecosystems and AI-based solutions and have numerous healthcare software solutions in our portfolio, telehealth systems in particular. In addition, we were able to assemble a large team to implement the project in a short time frame.
We were tasked with developing a multi-tenant SaaS environment that combines ML, IoT, and cloud-native technologies. The scope included the development of the following components:
Web interfaces for physicians and admins
Patient’s mobile app
Building a real-time telemetry data pipeline
Creating and training an ML model for data interpretation and analysis
Each tracking device collected massive telemetry from multiple sensors every second. However, this stream of numbers would tell doctors nothing. The main challenge was to analyze this raw data and interpret it correctly on the fly. To implement this process, we needed to:
Build and configure a secure data processing and transformation the process through all elements of the system
Train and configure an ML model that would detect abnormalities and identify problem areas
Implement a 3D engine that would display limb avatars on the physician’s interface and highlight problem areas
As the first step, our solution architect formed a high-level project design and solution vision on how to fulfill this ambitious project. The platform is based on cloud-native architecture and deployed on Microsoft Azure, using numerous services of this provider:
Azure Service Bus to build an elastic serverless pipeline designed to perform asynchronous operations on data streams in real-time, supporting high load in a highly available environment
Azure IoT Hub to connect, collect, and process telemetry from the devices
Azure API for FHIR to ensure storage and protection of medical data—the API aggregates data from disparate systems using the industry-standard HL7 FHIR
Azure Application Insights to provide administrators with a dashboard to analyze how the entire system performs
Azure SQL to store different types of data, including information regarding users of all roles and permissions, raw telemetry data and analytics reports, etc.
Azure Kubernetes Service (AKS) to quickly deploy a production-ready Kubernetes cluster in Azure
We had the necessary technical expertise to develop a custom graphics engine and implement it into the overall system. However, our architect emphasized that using an out-of-box solution such as 3D4Medical, one of the world’s most advanced 3D anatomy platforms, allowed it to meet all functional and non-functional requirements of the product and provided optimal effort, time, and expenses compared with a custom engine.
NIX data scientists built and trained an ML model that analyzed real-time streams of biometric data from IoT devices and determined deviations or anomalies in the musculoskeletal system. In addition, it used emerging techniques such as gait analysis to classify disease and localize problem areas.
We developed native mobile apps for both iOS and Android using Swift for iOS and Kotlin for Android. Using the apps, patients can connect with multiple medical devices and securely transmit health condition data to the cloud.
The functionality of the developed web app allows physicians to monitor and assess patients’ conditions and manage treatment and prescriptions. The development process was carried out according to relevant guidelines to ensure a high level of security. Software for physicians also includes appointment and treatment managing features.
The client received a cloud-based telehealth system with sophisticated AI-based analytics and an intuitive interface that has no analogs at that moment. The solutions provide advantages for both physicians and patients. They contribute to the early detection of health problems, increase treatment quality by intelligent assistance and remote tracking capabilities, and reduce costs for patients and healthcare providers.
Such solutions, combining several innovative technologies at once, open the door to the future of diagnostics and treatment, and the healthcare industry as a whole.
Thanks to the recommendation of experts to use a ready-made SDK to create 3D models, the client was able to save a significant amount of money that was invested in another project.
19 experts (Software Architect, Project Manager, Product Owner, Lead Developer, 5 Full Stack Developers, 2 Android Developers, 2 iOS Developers, 3 Test Engineers, DevOps Engineer, UI\UX Designer, DBA)
.NET, ReactJS, PostgreSQL, Docker, Kubernetes, Swift, Kotlin
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