Medical “Vampire” Robot Seeks Human Vein, Inserts Needle, Sucks Blood

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.

Venipuncture Device

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.

System Setup

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.

Efficacy

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.