HealthTech Industry Update | Telehealth Visits Lead to Fewer Follow-Up Visits Than Office Visits

The Epic Research study found that 16 out of 24 specialties had higher follow-up rates within 90 days of an initial office visit than a telehealth visit.

This concerned the medical areas:

  • mental health
  • physical medicine and rehabilitation
  • pain medicine

with  more than 20% higher follow-up rate after an in-person office appointment than after a telehealth appointment.

For the medical domains:

  • ophthalmology 
  • obstetrics and gynaecology 
  • podiatry
  • ear, nose and throat 
  • dermatology 
  • allergy
  • paediatric
  • internal medicine

had an at least 9% higher in-person follow-up rate after telehealth appointments than office appointments.

In future studies it will be checked as well both the complexity of visits between telehealth and in-person care and the effect that insurance coverage has on telehealth utilization.

Recommendations:

  • The government and policymakers should use them to inform future regulatory and funding efforts that affect the adoption of telehealth services. 
  • For payers, these findings suggest that telehealth can be a sufficient way to provide care, something that should be considered when determining coverage. 
  • Health systems, meanwhile, should continue offering telehealth as it may be patients’ preferred way of receiving care.

Have a look at the article in MedCityNews and the comments of Jackie Gerhart, chief medical officer of Epic Research.

https://medcitynews.com/2023/07/telehealth-healthcare-virtual-mental-primary-care/

HealthTech Knowledge Guide | What you should know about Clinical Trials

In EU for medical devices and Software of Class 2b and Class 3 and Class 3 in USA/FDA have to prove that all criteria of the:

is fulfilled. 

One point in this Regulation is to undergo Clinical Trials (or Clinical Studies or Clinical Investigations).

The safety, function and value-add of the Devices must be  Bench testing, Technical testing, Computer simulations, Animal studies must be checked and documented. Pre-clinical activities do not use human subjects in this case.

There are different pathways for the US and EU.

In the US, medical device manufacturers that want to pursue a clinical trial must obtain an Investigational Device Exemption (IDE).

Here as well a blog post by Thaumatec where you can have a look about the processing: https://thaumatec.com/knowledge/blog-posts/healthtech-industry-update-from-the-idea-to-a-medical-device/

In the EU MDR has 20 articles for clinical investigations of medical devices that are relevant. Within these articles, the regulation lays out three regulatory pathways manufacturers can take

During the premarket and postmarket phases of the device clinical trials may be executed. 

Early Pilot studies 

in the device development when nonclinical testing is unable to provide information on device functionality and clinical safety at this point of time.

Pivotal studies 

are used to gather definitive evidence of the safety and effectiveness of your medical device for a specific intended use. 

post-market surveillance 

includes both confirmatory and observational types of clinical activities. 

Observational clinical activities

Many post-market clinical activities are categorised as “observational” and they use non-interventional methods to collect data.

Some devices may need:

  • clinical data from all of these categories
  • many will not. 
  • low risk devices relying on well-known technology may not require any clinical investigations 

Here a nice video about clinical trials globally…

And here an article “Medical Device Clinical Trials: Regulatory Pathways & Study Types Explained” from  Jon Bergsteinsson in Greenlight Guru:

https://www.greenlight.guru/blog/medical-device-clinical-trials

Knowledge Database | IOT Connected Prototypes

Thaumatec had experienced a lot about the steps during the deployment of an IoT innovation and the prototyping phase. Most of our prototype projects have been done in an iterative and often rapid way.

There are several methods of industrial design prototyping: iterative, parallel, competitive, and rapid. These different methods of prototyping produce varying models of proof-of-concept during the product development process.

Iterative 

Iterative prototyping involves creating a prototype from the product design, testing it for usability and functionality, and then revising what didn’t work. After testing has concluded, the research team will design a new iteration and manufacture it for testing. The old iteration is then thrown out or set aside. Iterative prototyping is practical and allows for quick identification of challenging design problems but can be expensive and wasteful depending on the number of iterations required.

One kind of iterative prototyping is evolutionary prototyping, that removes the need for more than one iteration. The idea behind evolutionary prototyping is to gradually refine the first iteration as improvements are identified based on incoming feedback. Eventually, the first and only prototype becomes the final product after extensive machining and revising.

Rapid

Rapid prototyping is a more recent product design testing method that incorporates some aspects of the iterative process. This method is fast and accessible for product designers who can access CAD software and 3D printing technology in-house. Rapid prototyping utilizes innovative technologies—CAD software and 3D printing—to create seamless data transfer from computer to printer. This method is an affordable way to run usability and functionality tests on newly printed mockups.

Previous methods might take a few days to manufacture and compare iterations of the product depending on fabrication technology and communication requirements. Rapid prototyping is a process that could be minimized to a daily cycle where the new product iteration is designed/revised during the day and then printed overnight. 

Parallel 

On the other hand, parallel prototyping is a concept-based method where several design concepts are compared concurrently. Multiple designs are drafted and then compared to find the best versions before a physical prototype is manufactured. This method promotes creativity and conceptual ideation. Parallel prototyping can be expensive due to a large number of contributing factors.

Subsequently, there is a parallel prototyping version — competitive prototyping — where multiple design teams develop concepts independently. Competitive prototyping is useful for larger projects that have the potential for higher risk factors.

Competitive

Competitive prototyping is an approach in which two or more competing teams (organizations) develop prototypes during the early stages of a project (acquisition or procurement phase.

The competing prototypes are compared, and ultimately the one that best addresses the issue(s), problem(s), or challenge(s) is chosen). 

Prototype PoC projects can be handled like this:

Here are the main steps, we found out, which are the most important ones in this method.

How come from the idea to a concept ?

Every IoT project starts with an idea. Nowadays for producers it is possible to quickly turn those ideas and concepts into something real. 

For the concept it is important to have the most important requirements and key data is defined and checked, the details can be fine tuned later.

In many cases, a cheap processing board like Raspberry Pi or Arduino is enough for this purpose. For Connectivity often a physical cable to link the sensor to an standard IoT gateway is enough, although Wi-Fi, LoRa, NB-IOT or other radio technologies are essential already needed and the more likely option. The selection of the right connectivity technology is very important as it influences the IOT system behaviour and bottlenecks should be found, even in simple configuration.

Which Prototype variant to choose ?

Often rapid prototyping is used as it has become easier and cheaper. The Chinese manufacturers are even building in volumes of one.

But once you bring the proof of concept from your lab to the field can you really rely on the solution and chosen connectivity? Depending on the environment, you might think cellular connectivity is your best option but the investor or client does not like to have monthly fees and costs. So maybe to invest in a private LoRa network. Anyway it is better to find such conditions out as early as possible.

So better to have an approach which takes more time but allows more iterations and prevents failure.

Iterate and gain confidence in your idea 

If you have already made the proper investigation of the connectivity in Step 1 or you did a fine tuning in Step 2 then you have in most cases no big adaptations in front of you.

The most important questions are: can your chosen connectivity handle all issues around security, authentication, authorization, safety, performance, reliability, costs, useful feature set and final production ? 

But in case you still find out that there are gaps due to changing target and adapted ideas you run in new questions very fast and have to tune the plans and design.

Define scenarios, field tests and proof confidence 

By design, IoT devices are constrained which implies limited processing power, storage and bandwidth. 

Where you plan to physically deploy will be a factor: if you aim to put a miniature computer on every streetlight, it isn’t practical to visit every one of them every Tuesday to install a patch. Or, if you fit a sensor in the road which is then embedded under concrete, you only have one time to get it right.

Important for scale | do’s and dont’s

If you want to ship your product all over the world, you have to take steps 1,2 and 3 already. Care that you’ve built in connectivity that works for your global application and markets.

Here the topics are e.g. in case of cellular connectivity useability of SIM Cards in certain countries:

  • In Saudi Arabia, and a U.S. SIM won’t necessarily work in France. 
  • In some of the biggest growth markets, Saudi Arabia, Turkey and Brazil, governments don’t permit global or permanent roaming.
  • In case of LPWAN systems the question is are in the target markets public LoRa providers or do you have to create a private network.
  • Similar constraints are maybe due to country specific regulations in the field of confidentiality, security and safety. 

The model now which applies to connectivity, to let you link services and IOT-devices over the internet at industrial scale that you can start small and then flex your network as you go through the subsequent steps. 

When considering what technology to enable your IoT project to scale the network connectivity you need to look to the models developed for infrastructure as a service and computing elasticity.

For establishing private connectivity networks use mesh solutions as Wirepas or ZigBee to prevent costs on network or spot planning or look for technologies that can automate the set-up of an IoT network topology via simple API calls and that remove the manual, time consuming bespoke steps.

Consider technologies that can aggregate different bearer networks so that you can mix and match multiple different connectivity types, and avoid lock-in from one single communication service provider.

Knowledge Database | Test and Test automation | Different types and measures overview

How to find the problems, bugs and leaks before the clients, users or hackers do

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With the growing technology, there has been a massive change in the software testing industry with the help of newly upgraded tools and trends. These changes are aiming for shorter cycle times, a better product quality providing products to the market, and reduction of costs in development and maintenance. Looking at the evolution in the field of test technology and testing processes a lot of skills and expertise is required from the software testers as well in adapting due to the changes and challenges every day.

There are a lot of different types and approaches of testing the different systems to be released, considering:

  • Dependencies on the used development process and development phases of the product
  • Different conditions and states of the product in these phases
  • Interactions with surrounding systems and interfaces
  • Conditions of the environment in which the product will operate
  • Criteria of related standards and regulations
  • Usability and user experience
  • Safety and security aspects
  • Compatibility with previous versions of the product
  • Proof of delivery, meeting requirements and quality assurance

Main steps of defining and following the test process

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  1. Set the test requirements according to the contractual requirements (hardest requirements first to be considered)
  2. Break it down and consider to create a special test framework
  3. Test Strategy & project governance definition
  4. Define special tests and as well partners for the execution (e.g. from Client, special skills, trial & friendly users, regulatory support, …)
  5. Team setup
  6. Reporting tools setup
  7. Documentation setup
  8. Test Environment setup
  9. Test Case Generation
  10. Test Case Execution
  11. Result and Analysis
  12. Bug fixing
  13. Re-test
  14. Final documentation

BASE TEST TYPES

4 main types of testing approaches

The decisions of selecting the several types of how to test a given HW and/or SW product must be made during the general test planning as they are important related to requirements, effectiveness needed and available test environment, budgets, test time and available tools.

Manual testing

Manual testing is the process of manually testing the software for defects. It requires a tester to play the role of an end user whereby they use most of the application’s features to ensure correct behaviour. It refers to a test process in which a QA manually tests the software application in order to identify bugs. To do so, QAs follow a written test plan that describes a set of unique test scenarios.

Automated testing

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Automated tests provide much faster feedback when things go wrong. Faster feedback from automated tests (whether run locally or on a build server) makes it easier for developers to ensure that their changes don’t break existing work, and reduces the time wasted during integration.

Black box testing

Black box testing involves testing a system with no prior knowledge of its internal workings. A tester provides an input, and observes the output generated by the system under test.

White box testing

White box testing is a software evaluating method used to examine the internal structure, design, coding and inner-working of software. Developers use this testing method to verify the flow of inputs and outputs through the application, improving usability and design and strengthening security.

PROGRESS AND STAGE RELATED TYPES

during product development test phases.

PoC Proof of Concept test

Is proofing and justifying the ideas and design approaches for the new product. These tests are executed on a (simple) pre-product version which is tested to check if the assumptions are fulfilled and the main base functions of the planned solution are properly working and harmonised between each other. 

See as well out article: IOT Connected Prototypes | Overview and Experience

SW Module test

Module testing is a process where you need to test each unit of these modules to ensure they adhered to the best coding standards. Unless a module passes the testing phase, it cannot go for the application testing process. Module testing, component testing, helps to early detection of errors in application testing.

Bring up test

Board bring-up is a phased process whereby an electronics system, inclusive of assembly, hardware, firmware, and software elements, is successively tested, validated and debugged, iteratively, in order to achieve readiness for manufacture.

End to End testing (E2E)

End-to-end testing is a methodology used in the software development lifecycle (SDLC) to test the functionality and performance of an application under product-like circumstances and data to replicate live settings. The goal is to simulate what a real user scenario looks like from start to finish.

Field test

Field Validation Table (FVT) is a test design technique, which mainly helps for validating fields present in the application. This technique adds value to an application or project and gives very good test coverage for field validation. And this technique easily helps to find defects lying in the system or application.

Field trials

Field trials are real-life experiments which test directly whether proposed interventions actually work. This makes them powerful tools for gathering evidence for making policy. But, as with all research methods, they come with costs, such as time and resources.

Clinical trials

Clinical trials are research studies performed in people that are aimed at evaluating a medical, surgical, or behavioural intervention. They are the primary way that researchers find out if a new treatment, like a new drug or diet or medical device (for example, a pacemaker) is safe and effective in people.

Usability tests

Usability testing refers to evaluating a product or service by testing it with representative users. Typically, during a test, participants will try to complete typical tasks while observers watch, listen and take notes.

Acceptance test

This is a type of testing done by users, customers, or other authorised entities to determine application/software needs and business processes. 

Acceptance testing is the most important phase of testing as this decides whether the client approves the application/software or not which has mostly direct impact to payments, reputation and further engagement.

Test plan example | overview 

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If a new product is to be developed which consists of HW (e.g. one or more devices) and one or more SW parts, this HW is needed in early stages of the product and of course its development cycle has to start earlier as well to get the first samples for the protype. The SW devliveries have to be scheduled in several phases which make the code available in-sync with the HW stages of PoCs, first samples and prototype phase, and HW ready for production. The Integration and first testing scenarios have to focus on these areas which prevent expensive HW changes in the later stages. The special test cases to ensure use-ability, performance, KPIs and reliability could be in parallel with or part of the E2E real system configuration tests. The acceptance tests to proof the requirements have to be aligned with the customer before hand and are starting at Ready for Acceptance and ending with the acceptance approval which is as well allowing payments according the terms.

STRATEGY & INFRASTRUCTURE RELATED TYPES

Different scenarios on test infrastructure and supporting nodes at the different development stages and strategies

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SW offline test / SW test with interface simulations

An offline exam means an exam that can either be administered paper-based or offline using examination software systems, like Qorrect, in which the test is run within an examination facility with computers only locally connected, for example.

Program branch coverage tests

Branch coverage is a metric that indicates whether all branches in a codebase are exercised by tests. A “branch” is one of the possible execution paths the code can take after a decision statement (e.g., an if statement) gets evaluated. Special debugging tools or markers in the code can determine whether the branch was visited or not.

To calculate Branch Coverage, one has to find out the minimum number of paths which will ensure that all the edges are covered. In this case there is no single path which will ensure coverage of all the edges at once. The aim is to cover all possible true/false decisions.

Environment or testbed

A testing environment is a setup of software and hardware for the testing teams to execute test cases. In other words, it supports test execution with hardware, software and network configured. Test bed or test environment is configured as per the need of the Application Under Test.

SW in the Loop test SIL

Software-in-the-Loop testing, also called SiL testing, means testing embedded software, algorithms or entire control loops with or without an environment model on a PC, thus without ECU hardware. In fact, SiL Testing is an integral part of automotive software testing.

HW in the Loop test HIL

Hardware-in-the-loop testing provides a way of simulating sensors, actuators and mechanical components in a way that connects all the I/O of the ECU being tested, long before the final system is integrated. It does this by using representative real-time responses, electrical stimuli and functional use cases.

Product test with Simulators

A simulator creates an environment that simulates interfaces, content and protocols of a real device. 

It is a software or Software/Hardware that helps to test your product to test the interfaces, functions, and features not be connected to the real nodes and interfaces during operation.

The system reactions are pre-programmed per test case and need the full call flow scenario- and data model know-how from the test designers and programmers. Protocol test equipment is used to monitor and store the test results in compliance with interface standards and parameters.

Product test with Emulators

An emulator creates (emulates) an environment that mimics the behaviour and configurations of a real device (it acts like a real connected device, but sometimes in a more simple way).

It is software and Hardware that helps to test your product via the interfaces, functions, and features not connected to the real nodes and interfaces during operation. Examples are test equipment from Anritsu or Tektronix.

The emulator is e.g. supporting the interface standards and logic flow reactions during an early stage to help product vendors to test their products as long as no partner and corresponding nodes are still on the market or company internally available.

Real equipment E2E test

End-to-end testing is a methodology used in the software development lifecycle (SDLC) to test the functionality and performance of an application under product-like circumstances and data to replicate live settings. The goal is to simulate what a real user scenario looks like from start to finish.

TARGET & COVERAGE RELATED TYPES

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Important are the definitions which targets are needed to achieve for the best product quality. I must be aligned with the whole QA system and as well be focused on the key areas of clients requirements and expectations. 

Basic operation tests

Operational testing is a type of non-functional acceptance testing that confirms that a product, service, process or system meets operational requirements.

Examples are Load & Performance Test Operation, Security Testing, Backup and Restore Testing, and Failover Testing.

Functional tests

Functional testing is a type of software testing that validates the software system against the functional requirements/specifications. The purpose of Functional tests is to test each function of the software application, by providing appropriate input, verifying the output against the Functional requirements.

Non functional tests

Non-functional testing is the testing of a software application or system for its non-functional requirements which means the way a system operates, rather than specific behaviours of that system.

Functional requirements explain how the system must work, while non functional requirements explain how the system should perform.

Error / Scenarios tests

Scenario testing is a software testing activity that uses scenarios: 

  • hypothetical stories to help the tester work through 
  • a complex problem or test system 
  • The ideal scenario test is a credible, complex, compelling or motivating story. 
  • The outcome of which is easy to evaluate.
  • Error scenarios like power outage, alarms, data corruptions or wrong interface approaches can be be created by using simulators

Regression tests

Regression testing is testing existing software applications to make sure that a change or addition hasn’t broken any existing functionality.

Load testing

Some basic examples of load testing are: Testing a printer by transferring a large number of documents for printing. Testing a mail server with thousands of concurrent users. Testing a word processor by making a change in the large volume of data.

Stress tests

Stress testing (sometimes called torture testing) is a form of deliberately intense or thorough testing used to determine the stability of a given system, critical infrastructure or entity. It involves testing beyond normal operational capacity, often to a breaking point, in order to observe the results.

Performance tests

Performance testing is the practice of evaluating how a system performs in terms of responsiveness and stability under a particular workload. Performance tests are typically executed to examine speed, robustness, reliability, and application size.

Interaction tests

Interaction-based testing is a design and testing technique that emerged in the Extreme Programming (XP) community in the early 2000’s. 

Focusing on the behaviour of objects rather than their state, it explores how the object(s) under specification interact, by way of method calls, with their collaborators.

Interface tests

Interface Testing is defined as a software testing type which verifies whether the communication between two different software systems is done correctly. A connection that integrates two components is called interface. This interface in a computer world could be anything like API’s, web services, etc.

In the telecommunication are often interoperability tests between the different telecom vendors executed which are proof that the signalling standards are filufilled.

Certification tests

Justifies the usage of a product in a specified environment and under defined conditions.  The process for certification of a product is generally summed up in the steps:

  • Application (including testing of the product)
  • Evaluation (does the test data indicate that the product meets qualification criteria)
  • Decision (does a second review of the product application concur with the Evaluation)

This is a very important step and test type for Medical Devices (according MDR) and Common criteria for High Security requirements.

HARDENING TYPES

Hardening tests – security

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In computer security, hardening is usually the process of securing a system by reducing its surface of vulnerability, which is larger when a system performs more functions; in principle a single-function system is more secure than a multipurpose one.

Examples: Side channel attacks and channel attacks; Security measures: Secure SW writing which allows to mask and hide exchange of security keys and fault injection systems which simulate a breach.

Hardening tests – environmental

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Hardening of an electronic product concerns the resistance of this product against surrounding environments and effects like earthquake danger, theft danger, radiation impacts, mechanical load, extreme temperatures, humidity, usage in water and vacuum.

To test the stable performance of such products, the operation in a climatic chamber, systems to check robustness and simulating earthquakes, vacuum, water basins and generators for radiation and electromagnetic pulses.  

Radiation-hardened electronics, also called rad-hard electronics, are electronic components (circuits, transistors, resistors, diodes, capacitors, etc.), single-board computer CPUs, and sensors that are designed and produced to be less susceptible to damage from exposure to radiation and extreme temperatures (-55°C to 125°C).

In case of questions do not hesitate to contact us!

Healthtech Industry Update | Clinical Trials Have A Data Problem

Digital technology has a big advantage in clinical trials not to rely on patients’ paper intake forms and manual data entry into clinical systems only. Digitised processes present new opportunities to enhance the clinical experience e.g. virtual visits or e-Consent applications but adding disconnected tools increases complexity and costs, making it harder to get a holistic view of trial data.


While more data can lead to greater insights, it can also overwhelm and confuse research sites and data managers if managed incorrectly.

Here are some key challenges facing the industry today—and recommendations for overcoming them:


➡️️ Taming data overload because the overwhelming number of data sources and lack of access to the data originator make it difficult for study teams to determine which information to use and how to use it.


➡️ Enabling standardization: Without the proper measures and systems in place, standardization would require constant monitoring and updating for alignment across stakeholders.


➡️ Accelerating information flow for timely adjustments: Delays caused by manual data processes, however, could slow these necessary dosage adjustments.


➡️ Establishing a data foundation for digital trials: By working together to standardize data documentation processes and leverage advanced systems, sponsors, CROs, and research sites can access and interpret data faster and better than ever.

This expedites data collection and reduces human error, enabling processes to be automated and reconciled efficiently.

To maximize the digital clinical trial opportunity, it is imperative to establish a solid foundation of data collection and management best practices and capitalize on the advancements in data management technologies. Only then will we see the true potential of medical innovation as new treatments get to patients at an unprecedented pace.

You would like to know more details …
https://medcitynews.com/2023/07/clinical-trials-have-a-data-problem-heres-how-the-industry-can-solve-it/

Knowledge Database | Biometrics in computer vision systems 

Biometrics in computer vision is basically the combination of Image Processing and Pattern Recognition. Biometrics deals with the recognition of persons based on physiological characteristics, such as face, fingerprint, vascular pattern or iris, and behavioural traits, such as gait or speech.

Biometric technologies and computer vision are more and more needed to allow modern safe, fast and comfortable recognition, surveillance, protection and assistance services. Biometric systems are more and more relevant in applications which need visual, audio or other sensor data input to be able to collect these data and as well to recognize, analyse and steer the right expected actions.The applications are coming from many different industry domains for example healthcare, safety, surveillance, production, automotive, and many more. The sensors, cameras, and microphones are getting more and more safe, secure, accurate, robust and reliable and need to be integrated with adequate comparison, crosscheck and fusion functionality.

Computer Vision & Biometrics in Healthcare

In the last decades the healthcare industry has been supported by an ever increasing number of Computer Vision applications. One of the emerging fields in this scenario is biometric traits and related research that are typically aimed at security applications involving person authentication and identification. However, the increasing sensitiveness and image quality of the sensors available nowadays, along with the high accuracy and robustness achieved by the classification algorithms proposed nowadays, open new applicative horizons in the context of healthcare, to the aim of improving the supply of medical treatments in a more customised way, as well as computational tools for early diagnosis. The main implications of Computer Vision for medical usage are imaging analysis, predictive analysis and healthcare monitoring using biometrics in order to minimise false positives in the diagnostic process or control the treatment.

Following Devices & Sensors can been integrated in biometrics solutions:

🎦Biometrics cameras 

🎦3D Camera systems

🎦Iris scanners

🎦fingerprint sensors

🎦Microphones

🎦Health sensors (body temperature, blood-samples, heartbeat, blood pressure, …)

🎦Actuators

🎦Alarming systems

🎦Barring and lock systems

🎦Smart devices, watches

🎦Ultrasonic

🎦Radar and Lidar 

Biometrics | Some technical background

Biometric Authentication

Biometric systems rely on several discrete processes: enrolment, live capture, template extraction, and template comparison. 

The purpose of enrolment is to collect and archive biometric samples and to generate numerical templates for future comparisons.

 By archiving the raw samples, new replacement templates can be generated in the event that a new or updated comparison algorithm is introduced to the system.

 Practices that facilitate enrolment of high-quality samples are critical to sample consistency, and improve overall matching performance, which is particularly important for biometric identification by “one-to-many” search.

Template extraction requires signal processing of the raw biometric samples (e.g. images or audio samples) to yield a numerical template. Templates are typically generated and stored upon enrolment to save processing time upon future comparisons. Comparison of two biometric templates applies algorithmic computations to assess their similarity. Upon comparison, a match score is assigned. If it is above a specified threshold, the templates are deemed a match

Computer Vision and biometrics in different Industries

Computer vision technology is one of the most sought-after tech concepts these days. Raconteur reports that innovation is omnipresent in our lives, from driving cars to using search engines. We are going to dwell upon several popular fields for implementing computer vision solutions:

  • AR-enhanced images and videos
  • Robots in retail and supply chain
  • Advanced medical imaging tools
  • Tools to enhance OCR-ed images
  • Approaches to mitigate biases in sports
  • Techniques to boost agriculture industry
  • Facial recognition and access systems
  • Mood and thief detection
  • Iris matching and access control
  • Voice matching system
  • Fingerprint detection and identification
  • Payment and banking
  • Mobile recognition devices
  • Physical and safety solutions
  • Keyless locking systems
  • Area protection systems
  • Airport access systems
  • Surveillance and observation
  • Gesture and behaviour detection
  • Sleeping monitoring sensor observation 
  • Surgical head camera
  • Servant home robots
  • 24/7 patient monitoring
  • Operation room equipment
  • Robot and robotics solutions
  • Manufacturing and production quality control
  • and many more…..

Due to the many use cases for solutions with telemetry sensorics and data, a critical prerequisite to making the innovation a cross-industry trend is data growth worldwide. According to statistics, users share more than 3 billion images online daily. Built-in cameras and personal mobile devices generate data permanently. What is more, computing power for analysis of massive data has become available and affordable so far.

Computer Vision is using Machine Learning & Deep Learning the subareas in the field of Artificial Intelligence. 

This big amount of data makes it impossible to keep an overview about all tendencies, changes and aspects ongoing at any time and with best insight. Therefore AI technology is requested for analytics and evolutionary learning and fast and accurate visualisation or action triggers. 

Computer Vision & Machine Learning & Deep Learning evolution

Machine learning and computer vision are two fields that have become closely related to one another. Machine learning has improved computer vision about recognition and tracking. It offers effective methods for acquisition, image processing, and object focus which are used in computer vision. It is able to learn without being explicitly programmed.

In turn, Computer Vision has broadened the scope of machine learning. It involves a digital image or video, a sensing device, an interpreting device, and the interpretation stage. 

Machine learning is used in computer vision in the interpreting device and interpretation stage.

Deep Learning is a further step that the Network itself is capable of adapting to new data.  

Exploring and developing many PoC and product projects in these areas allows Thaumatec to support all industry domains with best experience and know how to develop, integrate and equip existing and new products with the not dispensable related SW elements.

If you should need more insight or any help, please contact us at
https://thaumatec.com/contact/

HealthTech industry Update | Access and Diversity in Clinical Trials

Physicians from underserved communities into research through a reimagined model, we can impact better health outcomes rooted in quality data that allows us to thrive from more diversity and better representation while providing patients with greater access to new care options.

🧑‍⚕️🧑‍⚕️🧑‍⚕️Clinical research partners must intentionally expand their reach to include investigators serving the people within these diverse and often underserved communities. This should be non-negotiable and integral to every research project plan.

To do so it is needed to:

🧑‍⚕️Building trust

🧑‍⚕️Empowering investigators

🧑‍⚕️Maintaining relationships with investigators

Conclusion is

🏥providing investigators with a strong infrastructure, top-notch support with day-to-day boots on the ground, and powerful, continuous training makes for solid and successful relationships. 

🏥A reimagined model will impact better health outcomes rooted in quality data that allows us to thrive from more diversity and better representation while providing patients with greater access to new care options.

https://medcitynews.com/2023/05/access-and-diversity-in-clinical-trials-requires-supporting-the-investigators/

Knowledge Database | The right IOT Operating System for your IOT product

The question is not which is the best in the world, it is the selection which one fits the best to your product. The first decision is which IOT functionality you are aiming:

  • IOT data collection, connectivity, remote controlled
  • IOT data collection, connectivity, immediate decisions, controlling
  • IOT data repository and IOT analytics

Here some overview of typical Operating System types for industrial use according function, with useability:

Embedded OS | IOT data collection, connectivity, remote controlled

This type of operating system is typically designed to be resource-efficient and reliable. Resource efficiency comes at the cost of losing some functionality or granularity that larger computer operating systems provide, including functions which may not be used by the specialized applications they run. Depending on the method used for multitasking, this type of OS is frequently considered to be a real-time operating system.

To be used in case of:

  • Embedded computer systems
  • Small machines with less autonomy
  • Device examples: Controllers, Smart Cards, Mobile devices, sensors, Car ECUs, M2M devices, …..
  • Compact and extremely efficient
  • Limited resources

Products commonly used:

  • INTEGRITY (RTOS)
  • VxWorks.
  • Linux, including RTLinux, Yocto (Linux distribution for IoT), MontaVista Linux
  • Embedded Android
  • iOS
  • Windows CE
  • MS-DOS or DOS Clones
  • Unison OS

Real time OS | IOT data collection, connectivity, immediate decisions, controlling

A RTOS is an operating system intended to serve real-time applications that process data as it comes in, typically without buffer delays. Processing time requirements & OS delay are measured in tenths of seconds or shorter increments of time. A real-time system is a time-bound system which has well-defined, fixed time constraints. Processing must be done within the defined constraints or the system will fail. They either are event-driven or time-sharing. Event-driven systems switch between tasks based on their priorities, while time-sharing systems switch the task based on clock interrupts. Most RTOSs use a pre-emptive scheduling algorithm.

To be used in case of:

  • deterministic nature of behaviour
  • Real time event handling and priority driven state / event coupling
  • specialized scheduling algorithms
  • Clock interrupt handling

Products commonly used:

  • INTEGRITY (RTOS)
  • VxWorks
  • Windows CE
  • DSP/BIOS
  • QNX
  • RTX
  • ROS
  • FreeRTOS (emb.)

Server OS | IOT data repository and IOT analytics 

A server operating system (OS) is a type of operating system that is designed to be installed and used on a server computer. It is an advanced version of an operating system, having features and capabilities required within a client-server architecture or similar enterprise computing environment. Some of the key features of a server operating system include:

  • Ability to access the server both in GUI and command-level interface
  • Execute all or most processes from OS commands
  • Advanced-level hardware, software and network configuration services
  • Install/deploy business applications and/or web applications
  • Provides central interface to manage users, implement security and other administrative processes
  • Manages and monitors client computers and/or operating systems

To be used in case of:

  • Virtual machine
  • Virtualization
  • large server warehouses
  • Micro Service based

Products commonly used:

  • Windows Server 
  • Mac OS X Server
  • Red Hat Enterprise Linux (RHEL)
  • SUSE Linux Enterprise Server
  • Debian, Ubuntu
  • CentOS
  • Gentoo
  • Fendora
  • ROS

Thaumatec has got a lot of experience with Operating Systems during the execution of many projects which required OS tuning. We helped the clients with PoC investigation, OS porting projects and product development to have the right OS in place.

HealthTech industry Update | Better Data Quality Means a better future for Public Health

Public health is heavily dependent on collecting and sharing accurate patient data. 

Standards for data collection and interoperability can move the needle toward better health data, but it is up to healthcare organisations.

Unfortunately, persistent data-quality issues beginning at the provider level continue to undermine population health. 

These include:

➡️ Inaccurate and incomplete patient records.

➡️ Duplicate patient records. 

➡️ When patient records are inaccurate or incomplete

➡️ Inconsistent data stored in disparate systems across different institutions. 

➡️ Outdated reporting for purposes of health equity and SDOH measures. 

Modern data platforms allow healthcare organisations to:

 💪Improve return on investment in their data

 💪Aggregate data access

 💪Free up staff time and resources with better tools and processes

 💪Enhance health equity and SDoH initiatives

 💪Be better prepared for the next public health crisis.  

Here some more information and an overview:

https://medcitynews.com/2023/06/better-data-quality-means-a-better-future-for-public-health/

If you would like to see or search more interesting posts, check our KNOWLEDGE DATA BASE | BLOGPOST DIRECTORY: https://thaumatec.com/knowledge/

Healthtech Industry Update | Digital Technology in Heart Health Care and Monitoring for Cardiac Patients

The Cardiac world has changed

in the last decade in many ways, digital technologies enable patients to obtain care closer to the home and doctors will diagnose cardiovascular disease earlier to assist carers, families, friends and patients undergoing and recuperating for major heart surgeries and rehabilitation processes.

Main focus

is on a holistic recovery journey with cardiovascular technologies and all equipment and methods for speed up detection and treatment for predictive checks, enabling more safe surgery, improving healing cycle, providing online resources, support and counselling of the patients.

There are trials ongoing with Artificial Intelligence and chatbots, big data, analytics and much more using a system framework and developing solutions using:

➡️ Big data that Cardiovascular Disorders can be detected

➡️ Artificial Intelligence and Therapy of cardiovascular disease

➡️ Alexa capabilities and voice technology for support

➡️ Apps for Telemedicine to consult periodically or fast the medics

Here some more information and an overview:

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