Editor’s note: Alena explains why it is worth supporting wearable biosensors with a cloud application and shows how a high-quality cloud application can make sensors bring more value due to better availability of data to medical staff and patients. If you are looking for a reliable vendor to bring an effective solution for your wearable biosensors, check ScienceSoft’s offering in medical device software development.
Recent studies show that the wearable biosensors market is growing and will reach $2.86 billion by 2025. And my experience with wearable devices and patient monitoring projects (for example, a mobile heart rate tracking app) shows that only those producers of wearable biosensors who augment their sensors with cloud applications will remain competitive in the growing market. Still, many manufacturers experience software-related technology gaps, so they are wary of adding a cloud application to their products, fearing to harm future users.
In the article, I explain why enriching your wearable biosensors with a cloud biosensor app is a good idea, refute widespread concerns you may have about it, and show how collaboration with a software vendor can be of help in the task.
When consulting producers of wearable biosensors, I help them figure out whether they should invest their time and money and expand towards creating cloud applications using smart technology. Generally, I mention the following benefits:
- Buying wearable biosensors with a ready-made cloud app, end customers can integrate them with their clinical applications quickly and easily. So, buyers do not have to look for a vendor to create needed software and save a considerable amount of time and money. As a result, your product becomes more competitive in the market.
- Placing wearable devices accompanied by a cloud biosensor application on the market shows maturity and experience in the industry and positively affects the image of the product and the company. This is a fruitful base for sales growth, which will allow you to occupy the desired market share.
- A cloud biosensor application can help optimize the work of a wearable device. For example, you can reduce the power consumption on the software side by controlling and adjusting the sampling frequency and data transmission. As a result, wearable devices will work without charging about 50% longer.
Below, you can see the simplified architecture of a typical cloud app solution for wearable biosensors that ScienceSoft offers to its customers. The standard IoT solution architecture is described in more detail in the article by my colleague Alex Grizhnevich.
Data gathered by biosensors goes directly to the HIPAA-compliant cloud biosensor application, where it is stored and analyzed. This cloud application feeds analyzed patient data to the EHR systems of care providers, where it can be accessed and managed. All data from the cloud biosensor app may be available via patient/hospital mobile and web applications, which facilitates access to clinical information for patients and medical staff.
You are likely to have certain concerns regarding the development of a cloud app for your wearable biosensors. For example, the most widespread worries of ScienceSoft’s customers are about harming the patients, violating personal data security, and having poor awareness about end-customer needs. Let’s see how they can be mitigated in collaboration with a dedicated vendor.
My customers often worry that incorrect data collection or errors in algorithms can lead to the inaccurate actions of a wearable device and wrongly suggested treatment for patients. For example, the app connected to the wearable glucometer detects an abnormal blood sugar level and notifies a patient to inject insulin, but in fact, the blood sugar level is within normal limits.
First of all, I’d like to point out that wearable biosensor cloud apps are not supposed to replace doctors. Their main goals are:
- Monitor patients’ activity and health conditions remotely.
- Provide better patient data visibility via live reports.
- Timely alert a doctor about a possible problem to increase treatment quality and speed.
However, low-quality data and algorithms errors may affect the quality of a doctor’s decisions, indeed. To minimize such a possibility, you may use recent advances in artificial intelligence, machine learning, and big data processing technologies to automate data recording/processing and support automatic monitoring with the help of a reliable vendor. These technologies also help achieve better accuracy of sensors.
Furthermore, I insist on providing quality assurance at different levels (biosensor, data ingestion and algorithms). A thorough approach to QA that covers various types of testing (functional testing, performance testing and compatibility testing) allows minimizing the possibility of harming patients.
The issue of data security in the healthcare industry is an acute one, since, for example, leakage of patient data can lead to huge financial and reputational losses. To improve data security, I suggest adhering to one of the main cybersecurity principles well formulated by Dmitry Kurskov, Head of Information Security Department at ScienceSoft:
“Applying cybersecurity measures once and forgetting about them forever is not a good strategy. The system security level should be regularly monitored, assessed, tested, and improved.”
Below, you can find a list of security measures relevant for wearable biosensor projects:
- Using security-first software architecture patterns.
- Using relevant permission settings.
- Performing regular vulnerability assessment and penetration testing.
- Conducting continuous network monitoring.
As my experience shows, it is difficult for producers of wearable biosensors to predict what functionality customers will need in software for wearable sensors besides the remote monitoring of patient health conditions and the data collection and processing.
As a business analyst and healthcare IT consultant, I believe that a thorough analysis of user needs and feature prioritization can help make the solution feature set viable. Also, you should provide for your wearable biosensors software to cater to the evolving needs and goals of healthcare organizations and their patients. For that, I advise you to ensure that your future cloud biosensor application is easily customizable so that buyers of wearable devices can adjust the system to their particular requirements.
Indeed, the development of software ecosystems for wearable biosensors is not an easy undertaking that requires skills in building a secure and scalable IoT architecture, big data storage and analytics, cloud development, and more. I believe, with those competencies in place and with a thought-out software development and QA strategy, all major problems like harming patients, violating personal data privacy and having poor awareness about end-customer needs can be mitigated. If you aren’t sure your competencies fit this list or if you want to know more details on how to avoid the major problems in your specific case, let me know.
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