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Recently, a wide spectrum of artificial intelligence (AI)–based applications in the broader categories of digital pathology, biomarker development, and treatment have been explored. In the domain of digital pathology, these have included novel analytical strategies for realizing new information derived from standard histology to guide treatment selection and biomarker development to predict treatment selection and response. In therapeutics, these have included AI-driven drug target discovery, drug design and repurposing, combination regimen optimization, modulated dosing, and beyond. Given the continued advances that are emerging, it is important to develop workflows that seamlessly combine the various segments of AI innovation to comprehensively augment the diagnostic and interventional arsenal of the clinical oncology community. To overcome challenges that remain with regard to the ideation, validation, and deployment of AI in clinical oncology, recommendations toward bringing this workflow to fruition are also provided from clinical, engineering, implementation, and health care economics considerations. Ultimately, this work proposes frameworks that can potentially integrate these domains toward the sustainable adoption of practice-changing AI by the clinical oncology community to drive improved patient outcomes.

Omnidirectional steerable forceps in keyhole procedures provide significant advantages in assisting medical practitioners with better motion coordination, improved dexterity, precision control, and reachability. However, most existing forceps lack the sense of interactive proprioception, imposing physical and cognitive challenges to the medical practitioners during manipulation. Herein, we report handheld steerable surgical forceps with two degrees-of-freedom equipped with skin-like soft stretchable strain sensors to determine the orientation and improve the perception. The performance of omnidirectional forceps integrated with sensory skin (OFISS) is characterized. Due to the reduced number of mechanical parts in the forceps by virtue of parallel continuum joints, the direct translation of motion from the proximal to the distal end is achieved. The distal parallel flexible joint enables a bending angle up to 40 and a bending radius of 7.5 mm. The hydrogel-based silver nanowire sensors mounted on the forceps like a stretchable skin show a maximum gauge factor of 11.8 under 80% strains. A mathematical model is developed to determine the tooltip orientation. The developed model validated with visual tracking shows an accuracy of 9097% for angular displacements up to 30 in all directions. Assisting medical practitioners in a clinical environment is demonstrated in a cadaveric setting by providing proprioceptive information of the tooltip through OFISS.

Tacrolimus is the cornerstone of immunosuppressive therapy after pediatric liver transplantation. However, reliance on the physician’s experience for dose titration, coupled with tacrolimus’s narrow therapeutic window and inter and intra-patient variability, often results in frequent under or over-dosing with detrimental patient outcomes. Existing predictive dose personalization models are not readily feasible for clinical implementation, as they require multiple measurements each day while the standard frequency is once daily. We developed CURATE.AI, a small-data artificial intelligence-derived platform, as a clinical decision support system to personalize doses using the patient’s own data obtained once a day. Retrospective dose personalization with CURATE.AI on 16 patients’ data demonstrated potential to enable patients to stay in the therapeutic range longer and reach the therapeutic range significantly earlier. Our findings support the testing of CURATE.AI in a prospective controlled trial as an aid for the physician’s decision on tacrolimus dose personalization after pediatric liver transplantation.

Wearable dry electrodes are needed for long-term biopotential recordings but are limited by their imperfect compliance with the skin, especially during body movements and sweat secretions, resulting in high interfacial impedance and motion artifacts. Herein, we report an intrinsically conductive polymer dry electrode with excellent self-adhesiveness, stretchability, and conductivity. It shows much lower skin-contact impedance and noise in static and dynamic measurement than the current dry electrodes and standard gel electrodes, enabling to acquire high-quality electrocardiogram (ECG), electromyogram (EMG) and electroencephalogram (EEG) signals in various conditions such as dry and wet skin and during body movement. Hence, this dry electrode can be used for long-term healthcare monitoring in complex daily conditions. We further investigated the capabilities of this electrode in a clinical setting and realized its ability to detect the arrhythmia features of atrial fibrillation accurately, and quantify muscle activity during deep tendon reflex testing and contraction against resistance., Reported wearable dry electrodes have limited long-term use due to their imperfect skin compliance and high motion artifacts. Here, the authors report an intrinsically conductive, stretchable polymer dry electrode with excellent self-adhesiveness for long-term high-quality biopotential detection.

This article presents a robotic needle positioning approach with a novel 4-DoF parallel positioner, two back-driveable 2-channel linear/rotational driver, and a machine–body interface. Being more compact and flexible, Ni–Ti alloy wire-based Bowden cable transmission is introduced to connect the positioner and the drivers. For this new mechanism, forward and inverse kinematics are derived, and the workspace is analyzed. The mechanism’s maximum incidence angle is 45 $^{\circ }$ , and the stroke of the slider is 41 mm. The structural size of one positioner is $\varnothing$ 70 mm × 45 mm. The compact size and lightweight of the positioner make it readily mountable on the skull or attached to other parts of the body. We fabricated a 3D printed proof-of-concept prototype of the system and tested its performance. The open-loop positioning accuracy of the slider and rotor is within $\pm$ 1 mm and from $-0.8^{\circ }$ to 1.5 $^{\circ }$ , respectively. The trajectory tracking error of the system is within 1.71 mm. The stiffness of the positioner in the x - and y -directions can be calculated as 9.03 and 11.91 N/mm, respectively. Finally, an image-guided navigation framework based on electromagnetic tracking demonstrates the feasibility of the proposed system on a phantom study.

Valves are largely useful for treatment assistance devices, e.g., supporting fluid circulation movement in the human body. However, the valves presently used in biomedical applications still use materials that are rigid, non-compliant, and hard to integrate with human tissues. Here, we propose biologically-inspired, stimuli-responsive valves and evaluate N-Isopropylacrylamide hydrogels-based valve (NPHV) and PAAm-alginate hydrogels-based valve (PAHV) performances with different chemical syntheses for optimizing better valve action. Once heated at 40 ∘C, the NPHV outperforms the PAHV in annular actuation (NPHV: 1.93 mm displacement in 4 min, PAHV: 0.8 mm displacement in 30 min). In contrast, the PAHV exhibits a flow rate change of up to 20%, and a payload of 100% when the object is at 100 ∘C. The PAHV demonstrated a completely soft, stretchable circular gripper with a high load-to-weight ratio for diversified applications. These valves are fabricated with a simple one-pot method that, once further optimized, can offer transdisciplinary applications.

Safer human-robot interactions mandate the adoption of proprioceptive actuation. Strain sensors can detect the deformation of tools and devices in unstructured and capricious environments. However, such sensor integration in surgical/clinical settings is challenging due to confined spaces, structural complexity, and performance losses of tools and devices. Herein, we report a highly stretchable skin-like strain sensor based on a silver nanowire (AgNW) layer and hydrogel substrate. Our facile fabrication method utilizes thermal annealing to modulate the gauge factor (GF) by forming multidimensional wrinkles and a layered conductive network. The developed AgNW-hydrogel (AGel) sensors sustain and exhibit a strain-sensitive profile (max. GF = ∼70) with high stretchability (200%). Due to its conformability, the sensor demonstrates efficacy in integration and motion monitoring with minimal mechanical constraints. We provide contextual cognizance of tooltip during a transoral procedure by incorporating AGel sensors and showing the fabrication methodology's versatility by developing a hybrid self-sensing actuator with real-time performance feedback.

The current state of the art of balloon catheters relies solely on the application of a predetermined quantity of mechanical strain to the balloon during diagnostic and therapeutic procedures. In some cases, the surgeons can use radioactive-contrasting agents and x-ray screening to identify the correct position and size of the inflated balloon. Otherwise, there is little information on the inflated size of the balloon catheter in the occluded lumen. This gap in quantitative feedback of the ballooning behavior needs to be addressed to ensure safe operation. With the advancement in technology and breakthrough in flexible electronics in recent years, kirigami, an ancient cutting, bending and folding technique, is explored in the stretchable sensing field due to its ability to transform 2D planar patterns 3D geometry structures. On top of that, kirigami can increase the mechanical strain by over 300% depending on the different cuts and folds and sensitivity over 80%. This manuscript will address this limitation of conventional balloon catheters by introducing strain sensing using kirigami technology to achieve a better, safer, and more efficient treatment procedure. Experimental results show that the change in normalized resistance of the sensor is directly proportional to the change in the size of the balloon.

The feasibility of using chip-based RFID designs as wireless sensor tags open a wide range of application possibilities in the field of robotics. However, multi-step lithography manufacturing and/or MEMS techniques are often required for the industrial-grade fabrication of such sensors. In this paper, we present a simple, home-based, two-step fabrication process to produce chipless RF-based wireless sensors. We use an office-based inkjet printer to produce the antenna traces using silver conductive ink. Kirigami-inspired designs are used to produce four sensors responsive to various mechanical stimuli commonly used for DIY robotic projects (contact, compression, extension, and bend). We demonstrate sensing and wireless transmission of the detected mechanical stimuli through the proposed chipless sensor tags with reliable consistency. The tags can be replicated quickly with the inkjet-printing method. This paper also contains analyses on the effects of varying the dimensions and electrical parameters of the tags. The developed antennas in this work can be used as wireless mechano-responsive sensors for robotic applications.

Intra-abdominal pressure (IAP) is closely correlated with intra-abdominal hypertension (IAH) and abdominal compartment syndrome (ACS) diagnoses, indicating the need for continuous monitoring. Early intervention for IAH and ACS has been proven to reduce the rate of morbidity. However, the current IAP monitoring method is a tedious process with a long calibration time for a single time point measurement. Thus, there is the need for an efficient and continuous way of measuring IAP. Herein, a stretchable capacitive pressure sensor with controlled microstructures embedded into a cylindrical elastomeric mold, fabricated as a pressure sensing sleeve, is presented. The sensing sleeve can be readily deployed onto intrabody catheter balloons for pressure measurement at the site. The thin and highly conformable nature of the pressure sensing sleeve captures the pressure change without hindering the functionality of the foley catheter balloon.

Wearable devices are gaining recognition for their use as a biosensor platform. Electrical impedance tomography (EIT) is one of the sensing techniques that utilizes wearable sensors as its primary data acquisition system. It measures the impedance or resistance at the peripheral (skin) level and calculates the conductivity distribution throughout the body. Even though the technology has existed for several decades, modern-day EIT devices are still costly and bulky. The paper proposes a novel low-cost kirigami-based wearable device that has soft PEDOT: PSS electrodes for sensing skin impedances. Simulation results show that the proposed kirigami structure for the bracelet has a large deformation during actuation while experiencing relatively lower stress. The paper also presents a comparative study on a few machine learning algorithms to classify hand gestures, based on the measured skin impedance. The best classification accuracy (91.49%) was observed from the quadratic support vector machine (SVM) algorithm with 48 principal components.

Two different types of soft actuators magnetic actuator and electroactive polymer (EAP) actuator are fabricated by using poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) as a conductive electrode. Magnetic actuators were fabricated through drop-casting of PEDOT:PSS and Fe3O4. Similarly, the EAP actuators were fabricated with ionic liquid/PVDF film sandwiched by two PEDOT:PSS film electrodes. In the magnetic actuator, the conductivity of the actuator decreases from 2160.0 to 1833.7 S/cm, as the ratio of PEDOT:PSS to Fe3O4 increases from 1:1 to 1:5. Meanwhile, the saturation magnetization increases, as the ratio increases from 1:1 to 1:5. For the EAP actuator, the PEDOT:PSS/xylitol films with a conductivity of 73.5 S/cm are employed for the electrical actuation. Overall, these actuators have the potential to be used in biomedical applications as soft actuators.

Flexible and stretchable tactile sensors that are printable, nonplanar, and dynamically morphing are emerging to enable proprioceptive interactions with the unstructured surrounding environment. Owing to its varied range of applications in the field of wearable electronics, soft robotics, human-machine interaction, and biomedical devices, it is required of these sensors to be flexible and stretchable conforming to the arbitrary surfaces of their stiff counterparts. The challenges in maintaining the fundamental features of these sensors, such as flexibility, sensitivity, repeatability, linearity, and durability, are tackled by the progress in the fabrication techniques and customization of the material properties. This review is aimed at summarizing the recent progress of rapid prototyping of sensors, printable material preparation, required printing properties, flexible and stretchable mechanisms, and promising applications and highlights challenges and opportunities in this research paradigm.

The tactile sensing technology has now progressed to the new developments in the field of robotics. In order to keep up with the trends, in this paper we have developed a soft fabric based tactile sensor which is incorporated with a 3D printed robotic hand for rehabilitation uses. Various types of tactile sensors were made with differences in the conductive material used. Conductive thread and conductive fabric based sensors were fabricated with the piezoresistive principle. On comparison with the conventional types of rigid tactile sensors, these newly fabricated sensors are advantageous in many ways in terms of their uncomplicated design, high sensitivity, lightweight and flexible nature. The 3D printed robotic hand has its inspiration from origami and its potential application in the rehabilitation process for stroke patients is validated in this paper.