The medical sensors market is predicted to be worth $1.7 billion by 2025, from an estimated $1.2 billion this year, according to a report published by Reportlinker. That represents a compound annual growth rate (CAGR) of 6.8 percent over the next five years.

Driving this healthy if unspectacular growth are rising incidents of chronic diseases, ageing populations in most countries, increased demand for home-based care devices, and technological advancements in the medical device industry.

The report separates the market by sensor type, product, application, end-user, and region. The market based on sensor type has been segmented into sensors for: temperature; blood oxygen; blood glucose; touch; imaging; motion; ECG; ingestible devices; and heart rate.

In terms of application, the report covers patient monitoring, diagnostic imaging, and medical implants and endoscopy, with products classed as either invasive or non-invasive.

The market for ingestible sensors will be among the biggest boom areas. These sensors are principally used in applications such as diagnosis, patient monitoring, and drug delivery.

Other hotspots include medical implants, driven by rising numbers of neurological disorders, improved clinical outcomes, and the development of implantable neuro-stimulation devices. Invasive products will be another key growth area, with growing demand for implantable cardioverter defibrillators, pacemakers, implantable loop recorders, and endoscopes, says the report.

The Asia Pacific medical sensors market will grow at the highest CAGR between 2020 and 2025, with rising awareness of digital healthcare among the growing elderly populations in Japan and South Korea, and new healthcare infrastructure investments in China, India, and Indonesia.

  • Key players operating in the medical sensors market include: Texas Instruments (US); TE Connectivity (Switzerland); First Sensor (Germany); Medtronics Plc (Ireland); NXP Semiconductors (Netherlands); Tekscan Inc (US); Amphenol Advanced Sensors (US); Proteus Digital Health (US); Sensirion (Switzerland); Cirtec Medical (US); Innovative Sensor Technology (Switzerland); Keller America (US); OmniVision Technologies (US); Masimo (US); TDK Sensors (Japan); Stanley Healthcare (US); EnviteC (Germany); and Merit Medical Systems (US).
  • As reported last year, a survey from analytics and AI software provider, Nyansa, based on a survey of Association for Executives in Healthcare Information Technology (AEHIT) members, revealed the security challenges facing healthcare professionals as the Internet of Things (IoT) is rolled out in hospitals.

According to that report, the monitoring and management of wireless biomedical devices are among the top priorities in healthcare organisations, in their quest to improve both productivity and the quality of patient care.

As connected biomedical technologies, such as medical sensors, electrocardiogram (EKG or ECG) devices, imaging systems, and patient monitoring devices spread, hospitals and clinics are becoming increasingly reliant on their wireless networks.

Infusion pumps, wearable sensors, bedside telemetry monitors, ultrasound solutions, and Wi-Fi based communications systems are all part of an increasingly complex picture. As a result, IT professionals are assuming a larger role in managing both the devices and their network connections.

  • Also in 2019, a report from Amoco research forecast that the global medical robotics market will grow at a CAGR of 15.5 percent to be worth $12.6 billion in 2025 – up from just under $4 billion in 2018. Robotics’ impact on the healthcare sector was spearheaded by Intuitive Inc, manufacturer of the Da Vinci surgical robot.
  • In related news, a new report from Mangrove Capital Partners on health tech investments says that AI and big data mean that we are moving beyond evidence-based healthcare and the traditional methodology of hypothesis-testing-conclusion.

The report says, “Rather than drawing and testing specific hypotheses, we can simply analyse the data that already exists and make predictions from the patterns that are unearthed. By collecting and connecting anonymised data on human health, from inside and outside the healthcare environment, we can analyse the relationships between different prevention or treatment techniques and patient outcomes.

“Furthermore, data can be used to assess all the variables that pertain to a specific individual and make precise, personalised recommendations that could not come from sample-based studies. AI, if developed and used appropriately, offers the potential for decision-making that is not only speedier and more accurate than that of humans, but also less biased and more rational.”