This article appeared in Electronic Design and has been published here with permission.
Telehealth is currently under the spotlight because of the COVID-19 pandemic. Doctors and nurses not only need to deal with the usual injuries and illnesses in addition to COVID-19, but also do so remotely in many cases. Cellular communication plays a critical role in the growth of telehealth, providing support for videoconferencing and remote patient monitoring (RPM) plus wireless communications.
These days, the internet of medical things (IoMT) is generating large amounts of information. 5G technology is needed to better address the amounts of information being generated (see figure below). To get a better idea about the latest telehealth trends, I spoke with Ee Huei Sin, vice president and general manager for General Electronics Measurement Solutions at Keysight Technologies.
Ee Huei Sin, vice president/general manager of Keysight Technologies’ General Electronics Measurement Solutions and the vice president of Keysight Education.
What are the current technology challenges hospital and healthcare facilities face regarding technology powering remote patient visits?
Telehealth today is limited by the network capacity to manage massive telehealth data. Ultra-reliable, high-speed, wide-bandwidth, and low-latency networks are required to support telehealth.
For example, remote patient monitoring needs to address real-time monitoring as well as streaming and analysis of patient data from massive medical devices. Virtual consultation via high-definition video is also coming and could very well dominate doctor/patient interactions.
Other applications of IoMT include the connected smart ambulance, where real-time streaming of patient data and emergency consultation via video allows remote support of on-site paramedics. Even remote surgery using robot control are being employed. This support along with emergency signal support requires extremely low latency besides real-time streaming on video and patient data.
Hospitals also need secure and efficient health-management systems to handle electronic medical records (EMRs), patient and hospital workflow, and connected devices. This requires a high level of network security and data protection for patient data privacy and security, especially when allowing external mobile access to EMRs.
The 5 C’s of IoT include connectivity, cybersecurity, continuity, coexistence, and compliance.
Does this technology meet current needs for bandwidth, connectivity, security, etc., and what needs to change?
5G technology was designed to support a large amount of connectivity and complex use cases such as telehealth. Enhanced mobile broadband (eMBB) is designed to deliver high bandwidth to support real-time 3D video as well as augmented-reality (AR) and virtual-reality (VR) applications.
5G supports high speeds of up to 20 Gb/s based on IMT-2020 and 1-GHz bandwidth, along with 10,000X greater traffic than the current 4G network can deliver. It also provides ultra-reliable low-latency communications (URLLC) for time-critical communication like remote robotic surgery, which requires extremely low latency. The latency for 4G is around 50 ms, but 5G can achieve latency well below 10 ms, and in best cases around 1-ms delays.
The massive machine-type communications (mMTC) enabled by 5G allows millions of devices to communicate at low data rates and at lower costs, and with less energy, in addition to providing the high-speed communication needed for other applications like video conferencing. 5G can support connection densities of 1 million devices per square kilometer versus around 4,000 devices for current 4G networks.
5G also supports network slicing for seamless resource management and better data security, and it fulfills diverse applications and service requirements. The new architecture enables service providers to build virtual and independent networks tailored to specific applications, versus “one-size-fits-all” in 4G.
What needs to change (from all stakeholders)?
As the 5G architecture advances, the platform for higher-frequency spectrum will take shape and unlock the full potential of 5G applications. Government support is accelerating adoption of 5G.
The challenge is to develop more 5G infrastructure to widen the coverage, especially in rural areas, to help local communities benefit from telehealth. This includes policies to encourage university research and university-industry collaboration on biomedical technology and other 5G advanced applications.
We expect more advanced applications such as medical services, robotics, and smart-home devices to be the main driving force for 5G demand. This can unleash more innovations in healthcare applications in tandem with other technologies such as artificial intelligence/machine learning, augmented/virtual reality and as well as edge computing in general. Lots of new medical device development is going on now, especially with respect to wearables and hearables that will leverage 5G technology for remote patient monitoring.
Keysight’s role is to help address the technical challenges in implementing and growing the adoption of telehealth. We offer end-to-end 5G solutions from early design to development, validation, manufacturing and the acceleration of commercial deployment. This includes software test automation and data-analytical tools used to improve the healthcare and connectivity system efficiency, as well as its performance. Network security and visibility monitoring solutions help minimize security breaches, increase patient privacy and improve network performance.
We recently acquired Eggplant, a firm that employed artificial intelligence and behavioral analytics to improve test creation and test execution. These technologies can be used to optimize the digital experience in the healthcare system.
How will this change following the COVID-19 pandemic?
Even before COVID-19, we have seen collaborations between hospital and telecommunication companies to setup 5G capabilities at medical centers. There’s also a clear convergence of consumer and medical devices, and rapid growth in IoMT for telehealth remote monitoring.
Consumer electronics companies have been entering the wearable medical device market as they move up to a higher value chain in medical applications. Medical device companies like Medtronic and ResMed are launching portable devices to be worn outside a medical facility to capture higher volumes in the consumer space.
Coronavirus has accelerated the rise of telehealth. Doctors and patients are turning to telehealth during the outbreak for routine medical care without risking a visit to hospital. This provides greater self-isolation, but it increases the need for medical services via telehealth.
Governments, insurers and healthcare providers are also pushing telehealth services with changes to policy and regulations, sometimes providing funding and other incentives. Some Singapore insurance companies have extended coverage for COVID-19, daily hospital benefits, and telemedicine claims during the “circuit breaker” period. In China, 5G-powered telemedicine, remote ultrasound and CT scanning are being utilized to tackle the shortage of medical personnel.
According to market analyst Frost & Sullivan, the demand for telehealth will soar this year as the COVID-19 pandemic disrupts the practice of healthcare delivery. The forecast is a seven-fold growth for the U.S. telehealth market by 2025, resulting in a 38% CAGR for the next five-year period, and 64% growth in 2020.
Asia-Pacific is expected to be the highest growth region due to a high rural population, improving healthcare scenarios, and high mobile adoption rate. Near-term trends for post-COVID-19 pandemic telehealth include more hospitals adopting 5G technology and expanding the telehealth services beyond teleconsultation to support more complex applications, addressing chronic disease management using smart devices and remote surgery using robotics as well as AR/VR in diagnosis and treatment.
The higher integration and communication will provide better patient care. More innovations in medical services will leverage 5G, AI and edge computing to allow for more immediate and actionable real-time patient monitoring. This will transform telehealth services and hopefully increase access services in rural areas.
Ee Huei Sin is the vice president/general manager of Keysight Technologies’ General Electronics Measurement Solutions, and the vice president of Keysight Education.
She is responsible in establishing the solutions unit with global presence and managing a portfolio of businesses focusing on measurement solutions for two broad base markets, the General Electronics and Education markets. The General Electronics segment provides solutions for consumer electronics, healthcare, and industrial & process control, and the Education ecosystem comprises both teaching and research labs.
Huei Sin possesses extensive international experience in managing a diverse portfolio of businesses in the general-purpose, electronics measurement and semiconductor industries, where she held various key global positions in marketing, manufacturing, order fulfillment, and business management. Prior to her current appointment, Huei Sin was the vice president/general manager of Keysight Technologies’ General-Purpose Electronics Measurement Division.
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This nearly autonomous medical robotic system uses ultrasonic imaging to locate a suitable forearm vein, then inserts a needle at the critical angle and distance, and finally draws a sample of blood.
This article appeared in Electronic Design and has been published here with permission.
Inserting a needle into the vein in someone’s arm and drawing a blood sample, or inserting an intravenous line, is a common medical procedure and often an essential first step in patient care. The challenge of obtaining successful venous access ranges from easy to very difficult depending on the subject’s veins and physiology as well as the skill of the medical technician. Oftentimes, it ends in a frustrating unsuccessful outcome that requires retries, delays and even additional help.
This clinical procedure is performed more than 1.4 billion times yearly in the United States. However, according to clinical studies, it fails in 27% of patients without visible veins, 40% of patients without palpable veins and 60% of emaciated patients. Instrumentation with ultrasound imaging is available to assist clinicians in locating the vein, but manual needle insertion under ultrasound guidance requires careful hand-eye coordination for steady placement and control of both the probe and needle. Near-infrared (NIR) imaging systems are also used, but they have a penetration depth of only about 3 mm and tend to be ineffective with obese patients.
Now, a team based at Rutgers University has developed and is field-testing a nearly autonomous robotic system that locates a likely suitable vein, inserts the needle and even draws the blood sample. This venipuncture device is designed to safely perform blood draws on peripheral forearm veins. The system combines ultrasound imaging and miniaturized robotics to identify suitable vessels for cannulation and robotically guide an attached needle toward what’s called the lumen center.
A clinician does the setup of general positioning of the machine with respect to the subject’s arm, sterilizing/wiping the target zone, applying ultrasound hydrogel and selecting the target vein’s center as displayed on a monitor. These coordinates are then used by the device to determine the necessary kinematics to ensure that the needle tip intersected the ultrasound imaging plane at the vessel center.
Once aligned and steady, the operator then initiates the insertion procedure, and the injection-axis carriage drives the attached needle tip forward at a 25-degree angle relative to the participant’s forearm to the target of the vein center, inserts the needle and draws a 5-ml blood sample.
The system consists of two major mechanical assemblies: a two-dimensional ultrasound probe on a linear motion carriage and the single-dimension needle thrust, both linked by a microcontroller for coordinated control (Fig. 1).
1. Exploded view and major functional components of the handheld venipuncture device.
Guidance and task execution employs a combination of force-vs.-displacement feedback profiling along with ultrasonic imaging (Fig. 2). Real-time analysis of that profile data indicates the likely success of the procedure, including the desirable sudden “breakthrough” that occurs as force suddenly drops over a short distance when the vein wall is pierced.
2. Robotic device set-up and operation: (a) Handheld venipuncture device. (b) Computer-aided design (CAD) displaying key components of the two-degree-of-freedom (DoF) device. Angle of insertion (θ) is fixed at 25 degrees. (c) Device operation: (i) Ultrasound (US) imaging plane provides a cross-sectional view of target vessel. (ii) Once a vessel is located by the device, the needle is aligned via the Z-axis motion (Zm) DoF motor; the Zm motor (blue arrow) is responsible for aligning the needle trajectory with the vessel depth (Z-axis) to ensure the needle tip reaches the vessel center exactly at the ultrasound imaging plane. (iii) Once trajectory is aligned, the needle is inserted via the injection motion (Inj m) DoF motor (green arrow) and automatically halted once the tip has reached the vessel center. (d) Device positioned over the upper forearm during the study. (e) Ultrasound image depicting the needle tip present in the target vessel after a successful venipuncture. Vessel wall is identified by a yellow dashed ellipse. The Z-axis in the image indicates the vessel depth and the Y-axis indicates the sagittal position of the vessel. Positions of the vessel and needle tip are recorded with respect to the ultrasound transducer head (top of image).
If the force/distance profile indicates the attempt will be unsuccessful (veins aren’t rigid, of course, and can move or roll during the process) or if no blood flows, the needle withdraws and the operator guides the machine to a new possible site. A graphical user interface shows the ultrasound image, force sensor, injection motor velocity and position profiles for both Z-axis and injection motors (Fig. 3).
3. The major displays of the graphical user interface (GUI) for the handheld venipuncture device software include the ultrasound image stream, force sensor, injection motor velocity, and desired versus actual position for both Z-axis and injection motors. The red line in the ultrasound image is the needle trajectory. This is where the needle will intersect the ultrasound imaging plane. The user is tasked with manually placing the device such that the imaged vessel (dark ellipse) is centered with the needle trajectory line.
The results thus far on a limited number of test subjects are favorable and comparable to or better than those of clinical standards. The overall success rate was 87% on all 31 participants and 97% on the 25 participants who had easy-access veins, with an average procedure time of 93 ± 30 seconds.
The researchers note that future versions of this system device could be extended to other areas of vascular access, such as IV catheterization, central venous access, dialysis and arterial line placement. Further, the system could be combined with an integral blood-assessment subsystem for an “all-in-one” blood-draw and test-result arrangement.
Details of the project are in the team’s paper “First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws” published in Technology (World Scientific). It focuses primarily on sensor data, profiles, algorithms and results and with less discussion of the machine’s actual construction. While that paper is behind a paywall, it’s also available here as an HTML page with a link to a downloadable PDF file.
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