The medical devices industry continues to be a hotbed of innovation, with activity driven by increased need for homecare, preventative treatments, early diagnosis, reducing patient recovery times and improving outcomes, as well as a growing importance in technologies such as machine learning, augmented reality, 5G and digitalisation. In the last three years alone, there have been over 450,000 patents filed and granted in the medical devices industry, according to GlobalData’s report on Artificial Intelligence in Medical Devices: Motion artefact analysis.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
150+ innovations will shape the medical devices industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the medical devices industry using innovation intensity models built on over 550,000 patents, there are 150+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, AI-assisted radiology, motion artefact analysis, and treatment evaluation models are disruptive technologies that are in the early stages of application and should be tracked closely. MRI image smoothing, AI-assisted EHR/EMR, and AI-assisted CT imaging are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are computer-assisted surgeries and 3D endoscopy, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the medical devices industry
Motion artefact analysis is a key innovation area in artificial intelligence
Motion artefacts are features that occur in diagnostic imaging as a result of a voluntary or involuntary patient movement during image acquisition. This occurs in multiple imaging modalities, and in the past the usual approach was to use multiple modality imaging such as PET-CT, where one image can be overlaid with another to give fixed reference points. Companies are increasing filing patents for new products which solves the problem by processing the immages using artificial intelligence, allowing for more accurate and quicker analysis.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 40+ companies, spanning technology vendors, established medical devices companies, and up-and-coming start-ups engaged in the development and application of motion artefact analysis.
Key players in motion artefact analysis – a disruptive innovation in the medical devices industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to motion artefact analysis
Source: GlobalData Patent Analytics
Heartflow is one of the leading patent filers in motion artefact analysis. Some other key patent filers in the medical devices industry include Siemens, Koninklijke Philips, Shanghai United Imaging Healthcare and Enlitic.
In terms of application diversity, Microsoft leads the pack, followed by Tencent Holdings and Lunit. By means of geographic spread, OtoNexus Medical Technologies held top spot, followed by Curemetrix and Lunit respectively.
Motion artefacts have been a recurring challenge to medical diagnostic imaging ever since radiology has become an essential component of modern medicine. Motion artefacts can introduce doubt and delay in a diagnosis, adversely affecting patient treatment outcome. In extreme cases, a motion artefact can cause a misdiagnosis, either missing a pathology in the tissue, or falsely identifying a tissue pathology. In conventional image analysis, for example, upwards of 50% of mammograms can be falsely interpreted, leading to cancers being missed or unnecessary invasive procedures being carried out. The use of artificial intelligence in addressing the motion artefact issue has the potential to greatly improve the accuracy of diagnoses.
To further understand the key themes and technologies disrupting the medical devices industry, access GlobalData’s latest thematic research report on Medical Devices.