The healthcare industry continues to be a hotbed of innovation, with activity driven by telemedicine, real-time diagnostics, smart hospitals, and access to digital therapies, and the growing importance of technologies such as artificial intelligence (AI), the internet of things (IoT), augmented reality (AR), robotics and data management practices. In the last three years alone, there have been over 106,000 patents filed and granted in the healthcare industry, according to GlobalData’s report on Artificial Intelligence in Healthcare: Vehicle driver physiological monitoring.
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.
200+ innovations will shape the healthcare industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the healthcare industry using innovation intensity models built on over 443,000 patents, there are 200+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, drug delivery device security, microscopic image analysis models, and cellular imaging techniques are disruptive technologies that are in the early stages of application and should be tracked closely. Smart balloon catheters, automated immunoassay analysers, and AI-assisted MRI are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are smart fitness training system and non-invasive physiological monitoring, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the healthcare industry
Vehicle driver physiological monitoring is a key innovation area in artificial intelligence
Vehicle driver physiological monitoring devices are smartphone-powered in-vehicle measurement systems that keep track of a driver's physiological signals such as breathing, eye blinking, heart rate, and heart rate variation. The physiological signals will be used to detect the onset of driver fatigue, which is crucial for timely application of drowsiness countermeasures, as driver fatigue is one of the major factors causing traffic accidents.
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 240+ companies, spanning technology vendors, established healthcare companies, and up-and-coming start-ups engaged in the development and application of vehicle driver physiological monitoring.
Key players in vehicle driver physiological monitoring – a disruptive innovation in the healthcare 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 vehicle driver physiological monitoring
Source: GlobalData Patent Analytics
NIKE is one of the leading patent filers in the field of vehicle driver physiological monitoring. Some other key patent filers in the field include Koninklijke Philips and Samsung Group.
In terms of application diversity, adidas leads the pack, followed by INRIX and Applied Lifesciences & Systems. By means of geographic reach, 3M Co holds the top position, followed by Applied Lifesciences & Systems and The Cleveland Clinic Foundation in second and third spots, respectively.
Driver mistake is a key contributor to car accidents and fatalities. Many of the collisions are caused by poor driver cognition as a result of exhaustion, sleepiness, stress, or mental burden. Physiological data such as heart rate and breathing rate are important for assessing a vehicle driver's cognitive state. Automated technologies are gradually taking away the driver's duty for safe vehicle control. Worries, however, remain that during times of highly automated driving, a driver's situation awareness, mental workload, and concentration levels may be compromised, resulting in a lower capacity to reclaim control of the vehicle safely when certain control features are later restored to the driver. In such cases, physiological monitoring may be required to check the driver's status and ensure that the driver is appropriately attentive and aware.
To further understand how artificial intelligence is disrupting the healthcare industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Healthcare.