A Dallas digital health startup needed a compliant MVP for personalised rehab at home. In 6 months, the team shipped a patient app, a therapist web app and wearable-sensor tracking. Therapists now adjust each plan from real joint motion data.
Physical rehab is hard to personalise. It is even harder to track once the patient leaves the clinic. A Dallas digital health startup wanted fully personalised remote physiotherapy, and this remote physiotherapy app development project turned their care model into a working product.
The platform has three parts: a cross-platform patient app, a web app for therapists and admins, and a HIPAA-compliant back end on AWS. The apps read Xsens DOT wearable sensors to measure joint range of motion and show therapy progress. A fully functional MVP was ready within 6 months.
The founders saw clear drawbacks in traditional rehab. They wanted exercises and progress tracking for each patient in one digital platform.
Their care model mixes offline and online rehab. A therapist assesses the patient in person first. After that, the therapist gives continuous online feedback and adjusts the program to the patient's performance.
That model needs objective data: how far a joint moves today, compared with earlier readings and the target. So the product had to join wearable sensors, a patient app, a therapist web app and a back end built for protected health information. The first goal was an MVP that real users could try.
A 13-person team covered product, compliance and engineering: a project manager, a business analyst, a regulatory compliance consultant, a UX/UI designer, 2 Xamarin developers, 2 front-end developers, 4 back-end developers and a QA engineer. It drew on our healthcare software development practice.
The team analysed the market and competing products, interviewed stakeholders and studied patient needs.
Research turned into requirements. The team mapped out the features and prioritised them for the MVP.
Software engineers designed a HIPAA-compliant architecture for the platform, with a regulatory compliance consultant on the project team.
The team built the patient app, the platform and the web app for admins and therapists. The fully functional MVP went to users, and their feedback shaped the next stage.
After that feedback, the startup entrusted the software evolution to us: better sensor algorithms, stability work, UI changes and performance fixes.
Every feature serves one goal: rehab fitted to each patient on a remote physical therapy platform.
Physical therapists create an in-app plan for each patient. The patient knows what to do, and the therapist can change the plan as progress data comes in.
Detailed video instructions show patients how to perform each exercise at home.
Patients and therapists see sensor range-of-motion data, program completion stage, minutes spent exercising, completed sessions and session history.
Text chat between patients and therapists keeps feedback continuous between in-person visits.
Articles and videos on musculoskeletal therapy help patients understand their condition.
A complementing web app gives admins and therapists access to the platform, where therapists create plans and review progress data.
The wearable sensors stream joint readings to the patient app. The app turns them into range-of-motion values and sends them to the back end. Therapists see them in their web app next to the patient's plan and history.
The patient app is a cross-platform mobile app development build, so one codebase serves both phone platforms. The therapist web app and the back end come from our Angular development company and Node.js development company teams. On AWS, compute runs the back end and the web app, and storage holds the library of exercise videos and images.
Data is encrypted on devices and on AWS, and every transfer runs over SSL. If you are scoping a HIPAA-compliant physiotherapy app, the HHS overview of the HIPAA Security Rule lists the safeguards expected for electronic health data.
Challenge. Therapists can only adjust a plan if the range-of-motion (ROM) readings are accurate. The vendor's default Xsens DOT motion capture algorithms were not tuned for the joints this care model tracks.
Decision. The team proposed proprietary algorithms built for knee joints and low back mobility, the two areas the startup treats.
Implementation. The app measures a joint's ROM, then compares it with the patient's earlier readings and the therapist's target. After user feedback on the MVP, the team also improved algorithm stability, app performance and the UI, and fixed two issues that hurt measurements:
The startup got a ready-to-market MVP and kept evolving the product with us. Users of the platform reported the outcomes below; the measurement method, sample size and period were not published.
Sensor-based rehab is a field we know well. On the connected rehabilitation platform, four motion sensors on a slant board stream live data to clinicians, with software documentation prepared for an FDA 510(k) submission.
The difference: that project turned custom hardware into a clinical product, while this one built a home-care product on off-the-shelf wearables. If your product sits between the two, the healthcare software development team can map the fastest route to an MVP.
Yes. This platform reads Xsens DOT wearable sensors to measure joint range of motion. The team replaced the vendor's default algorithms with ones built for knee and low back mobility. It then fixed sensor connection, data streaming and patient orientation issues that affect accuracy.
This one took 6 months to a fully functional MVP. That covered market and user research, requirements, a HIPAA-compliant architecture, and the patient app, platform and therapist web app. Your timeline depends on the number of platforms and how custom the sensor work is.
It depends on scope: the number of platforms, sensor integration, custom algorithms and compliance needs. The fastest way to a reliable estimate is a short discovery of your care model and feature priorities. That is how this project started.
A regulatory compliance consultant worked on the team from the start, and engineers designed the architecture to be HIPAA-compliant. Data is encrypted on devices and on AWS. Every data transfer runs over SSL.
Here it has three parts. Wearable sensors stream to a cross-platform patient app, which computes range of motion. A back end on AWS stores the data and the exercise media. A web app lets therapists build plans and review progress.
This one had 13 people across product, compliance and engineering: a project manager, a business analyst, a compliance consultant, a UX/UI designer, 2 mobile developers, 2 front-end developers, 4 back-end developers and a QA engineer.
Yes. After user feedback on the MVP, the startup entrusted the software evolution to us: better motion algorithms, stability and performance work, and UI improvements. If you need extra capacity instead, you can [hire Node.js developers](/hire-nodejs-developers) for your back end.
AngularJS
Node.js
Amazon EC2
Amazon S3
A US medical technology startup had a sensor-equipped slant board prototype and a tight deadline. We built the firmware, iOS, Android and web apps and AWS back end for a connected rehabilitation platform, plus the software documents for its FDA 510(k) submission.
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We can take your care model to a HIPAA-compliant MVP, then make the sensor readings accurate enough for therapists to act on.
