A tactile sensing system capable of recognizing objects based on bioinspired self-sensing soft pneumatic actuator.

Tactile sensors play an important role when robots perform contact tasks, such as physical information collection, force or displacement control to avoid collision. For these manipulations, excessive contact may cause damage while poor contact cause information loss between the robotic end-effector and the objects. Inspired by skin structure and signal transmission method, this paper proposes a tactile sensing system based on the self-sensing soft pneumatic actuator (S-SPA) capable of providing tactile sensing capability for robots. Based on the adjustable height and compliance characteristics of the S-SPA, the contact process is safe and more tactile information can be collected. And to demonstrate the feasibility and advantage of this system, a robotic hand with S-SPAs could recognize different textures and stiffness of the objects by touching and pinching behaviours to collect physical information of the various objects under the positive work states of the S-SPA. The result shows the recognition accuracy of the fifteen texture plates reaches 99.4%, and the recognition accuracy of the four stiffness cuboids reaches 100%by training a KNN model. This safe and simple tactile sensing system with high recognition accuracies based on S-SPA shows great potential in robotic manipulations and is beneficial to applications in domestic and industrial fields.

Treatment with robot-assisted gait trainer Walkbot along with physiotherapy vs. isolated physiotherapy in children and adolescents with cerebral palsy. Experimental study.

BACKGROUND: Improving walking ability is a key objective in the treatment of children and adolescents with cerebral palsy, since it directly affects their activity and participation. In recent years, robotic technology has been implemented in gait treatment, which allows training of longer duration and repetition of the movement. To know the effectiveness of a treatment with the robotic-assisted gait trainer Walkbot combined with physiotherapy compared to the isolated physiotherapy treatment in children and adolescents with cerebral palsy, we carried out a clinical trial. METHODS: 23 participants, were divided into two groups: experimental and control. During 5 weeks, both groups received their physiotherapy sessions scheduled, in addition experimental group received 4 sessions per week of 40 min of robot. An evaluation of the participants was carried out before the intervention, at the end of the intervention, and at follow-up (two months after the end of the intervention). Gait was assessed with the Gross Motor Function Measure-88 dimensions D and E, strength was measured with a hydraulic dynamometer, and range of motion was assessed using the goniometer. A mixed ANOVA was performed when the assumptions of normality and homoscedasticity were met, and a robust mixed ANOVA was performed when these assumptions were not met. Statistical significance was stipulated at p < 0.05. For the effect size, η2 was calculated. RESULTS: Significant differences were found regarding the time x group interaction in the Gross Motor Function Measure-88 in dimension D [η2 = 0.016], in the flexion strength of the left [η2 = 0.128] and right [η2 = 0.142] hips, in the extension strength of the right hip [η2 = 0.035], in the abduction strength of the left hip [η2 = 0.179] and right [η2 = 0.196], in the flexion strength of the left knee [η2 = 0.222] and right [η2 = 0.147], and in the range of motion of left [η2 = 0.071] and right [η2 = 0.053] knee flexion. CONCLUSIONS: Compared to treatments without walking robot, physiotherapy treatment including Walkbot improves standing, muscle strength, and knee range of motion in children and adolescents with cerebral palsy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04329793. First posted: April 1, 2020.

Merging sociality and robotics through an evolutionary perspective.

Robotics, using social mechanisms like hormonal modulation, may accelerate our understanding of core sociality principles.

Bilateral Back Extensor Exosuit for multidimensional assistance and prevention of spinal injuries.

Lumbar spine injuries resulting from heavy or repetitive lifting remain a prevalent concern in workplaces. Back-support devices have been developed to mitigate these injuries by aiding workers during lifting tasks. However, existing devices often fall short in providing multidimensional force assistance for asymmetric lifting, an essential feature for practical workplace use. In addition, validation of device safety across the entire human spine has been lacking. This paper introduces the Bilateral Back Extensor Exosuit (BBEX), a robotic back-support device designed to address both functionality and safety concerns. The design of the BBEX draws inspiration from the anatomical characteristics of the human spine and back extensor muscles. Using a multi-degree-of-freedom architecture and serially connected linear actuators, the device's components are strategically arranged to closely mimic the biomechanics of the human spine and back extensor muscles. To establish the efficacy and safety of the BBEX, a series of experiments with human participants was conducted. Eleven healthy male participants engaged in symmetric and asymmetric lifting tasks while wearing the BBEX. The results confirm the ability of the BBEX to provide effective multidimensional force assistance. Moreover, comprehensive safety validation was achieved through analyses of muscle fatigue in the upper and the lower erector spinae muscles, as well as mechanical loading on spinal joints during both lifting scenarios. By seamlessly integrating functionality inspired by human biomechanics with a focus on safety, this study offers a promising solution to address the persistent challenge of preventing lumbar spine injuries in demanding work environments.

An Embedded Electromyogram Signal Acquisition Device.

In this study, we design an embedded surface EMG acquisition device to conveniently collect human surface EMG signals, pursue more intelligent human-computer interactions in exoskeleton robots, and enable exoskeleton robots to synchronize with or even respond to user actions in advance. The device has the characteristics of low cost, miniaturization, and strong compatibility, and it can acquire eight-channel surface EMG signals in real time while retaining the possibility of expanding the channel. This paper introduces the design and function of the embedded EMG acquisition device in detail, which includes the use of wired transmission to adapt to complex electromagnetic environments, light signals to indicate signal strength, and an embedded processing chip to reduce signal noise and perform filtering. The test results show that the device can effectively collect the original EMG signal, which provides a scheme for improving the level of human-computer interactions and enhancing the robustness and intelligence of exoskeleton equipment. The development of this device provides a new possibility for the intellectualization of exoskeleton systems and reductions in their cost.

Therapy effect on hand function after home use of a wearable assistive soft-robotic glove supporting grip strength.

BACKGROUND: Soft-robotic gloves with an assist-as-needed control have the ability to assist daily activities where needed, while stimulating active and highly functional movements within the user's possibilities. Employment of hand activities with glove support might act as training for unsupported hand function. OBJECTIVE: To evaluate the therapeutic effect of a grip-supporting soft-robotic glove as an assistive device at home during daily activities. METHODS: This multicentre intervention trial consisted of 3 pre-assessments (averaged if steady state = PRE), one post-assessment (POST), and one follow-up assessment (FU). Participants with chronic hand function limitations were included. Participants used the Carbonhand glove during six weeks in their home environment on their most affected hand. They were free to choose which activities to use the glove with and for how long. The primary outcome measure was grip strength, secondary outcome measures were pinch strength, hand function and glove use time. RESULTS: 63 patients with limitations in hand function resulting from various disorders were included. Significant improvements (difference PRE-POST) were found for grip strength (+1.9 kg, CI 0.8 to 3.1; p = 0.002) and hand function, as measured by Jebson-Taylor Hand Function Test (-7.7 s, CI -13.4 to -1.9; p = 0.002) and Action Research Arm Test (+1.0 point, IQR 2.0; p≤0.001). Improvements persisted at FU. Pinch strength improved slightly in all fingers over six-week glove use, however these differences didn't achieve significance. Participants used the soft-robotic glove for a total average of 33.0 hours (SD 35.3), equivalent to 330 min/week (SD 354) or 47 min/day (SD 51). No serious adverse events occurred. CONCLUSION: The present findings showed that six weeks use of a grip-supporting soft-robotic glove as an assistive device at home resulted in a therapeutic effect on unsupported grip strength and hand function. The glove use time also showed that this wearable, lightweight glove was able to assist participants with the performance of daily tasks for prolonged periods.

Propulsion mechanism of artificial flagellated micro-swimmers actuated by acoustic waves-theory and experimental verification.

This work examines the acoustically actuated motions of artificial flagellated micro-swimmers (AFMSs) and compares the motility of these micro-swimmers with the predictions based on the corrected resistive force theory (RFT) and the bar-joint model proposed in our previous work. The key ingredient in the theory is the introduction of a correction factorKin drag coefficients to correct the conventional RFT so that the dynamics of an acoustically actuated AFMS with rectangular cross-sections can be accurately modeled. Experimentally, such AFMSs can be easily manufactured based on digital light processing of ultra-violet (UV)-curable resins. We first determined the viscoelastic properties of a UV-cured resin through dynamic mechanical analysis. In particular, the high-frequency storage moduli and loss factors were obtained based on the assumption of time-temperature superposition (TTS), which were then applied in theoretical calculations. Though the extrapolation based on the TTS implied the uncertainty of high-frequency material response and there is limited accuracy in determining head oscillation amplitude, the differences between the measured terminal velocities of the AFMSs and the predicted ones are less than 50%, which, to us, is well acceptable. These results indicate that the motions of acoustic AFMS can be predicted, and thus, designed, which pave the way for their long-awaited applications in targeted therapy.

A review of bioinspired dry adhesives: from achieving strong adhesion to realizing switchable adhesion.

In the early twenty-first century, extensive research has been conducted on geckos' ability to climb vertical walls with the advancement of microscopy technology. Unprecedented studies and developments have focused on the adhesion mechanism, structural design, preparation methods, and applications of bioinspired dry adhesives. Notably, strong adhesion that adheres to both the principles of contact splitting and stress uniform distribution has been discovered and proposed. The increasing popularity of flexible electronic skins, soft crawling robots, and smart assembly systems has made switchable adhesion properties essential for smart adhesives. These adhesives are designed to be programmable and switchable in response to external stimuli such as magnetic fields, thermal changes, electrical signals, light exposure as well as mechanical processes. This paper provides a comprehensive review of the development history of bioinspired dry adhesives from achieving strong adhesion to realizing switchable adhesion.

Active Neural Network Control for a Wearable Upper Limb Rehabilitation Exoskeleton Robot Driven by Pneumatic Artificial Muscles.

Pneumatic artificial muscle (PAM) has been widely used in rehabilitation and other fields as a flexible and safe actuator. In this paper, a PAM-actuated wearable exoskeleton robot is developed for upper limb rehabilitation. However, accurate modeling and control of the PAM are difficult due to complex hysteresis. To solve this problem, this paper proposes an active neural network method for hysteresis compensation, where a neural network (NN) is utilized as the hysteresis compensator and unscented Kalman filtering is used to estimate the weights and approximation error of the NN in real time. Compared with other inversion-based methods, the NN is directly used as the hysteresis compensator without needing inversion. Additionally, the proposed method does not require pre-training of the NN since the weights can be dynamically updated. To verify the effectiveness and robustness of the proposed method, a series of experiments have been conducted on the self-built exoskeleton robot. Compared with other popular control methods, the proposed method can track the desired trajectory faster, and tracking accuracy is gradually improved through iterative learning and updating.

A randomized cross-over study protocol to evaluate long-term gait training with a pediatric robotic exoskeleton outside the clinical setting in children with movement disorders.

Individuals with neuromuscular disorders display a combination of motor control deficits and lower limb weakness contributing to knee extension deficiency characterized by exaggerated stance phase knee flexion. There is a lack of evidence for long-term improvement of knee extension deficiency with currently available clinical treatment programs. Our previous work testing a wearable robotic exoskeleton with precisely timed assistive torque applied at the knee showed immediate increases in knee extension during walking for children with cerebral palsy, which continued to improve over an acute practice period. When we applied interleaved assistance and resistance to knee extension, we observed improvements in knee extension and increased muscle activation indicating the potential for muscle strengthening when used over time. There is a need for additional, high-quality trials to assess the impact of dosage, intensity and volume of training necessary to see persistent improvement in lower limb function for these patient populations. This randomized crossover study (ClinicalTrials.gov: NCT05726591) was designed to determine whether 12 weeks of overground gait training with a robotic exoskeleton outside of the clinical setting, following an initial in clinic accommodation period, has a beneficial effect on walking ability, muscle activity and overall motor function. Participants will be randomized to either complete the exoskeleton intervention or continue their standard therapy for 12 weeks first, followed by a crossover to the other study component. The primary outcome measure is change in peak knee extension angle during walking; secondary outcome measures include gait speed, strength, and validated clinical scales of motor function and mobility. Assessments will be completed before and after the intervention and at 6 weeks post-intervention, and safety and compliance will be monitored throughout. We hypothesize that the 12-week exoskeleton intervention outside the clinical setting will show greater improvements in study outcome measures than the standard therapy.

Bionic e-skin with precise multi-directional droplet sliding sensing for enhanced robotic perception.

Electronic skins with deep and comprehensive liquid information detection are desired to endow intelligent robotic devices with augmented perception and autonomous regulation in common droplet environments. At present, one technical limitation of electronic skins is the inability to perceive the liquid sliding information as realistically as humans and give feedback in time. To this critical challenge, in this work, a self-powered bionic droplet electronic skin is proposed by constructing an ingenious co-layer interlaced electrode network and using an overpass connection method. The bionic skin is used for droplet environment reconnaissance and converts various dynamic droplet sliding behaviors into electrical signals based on triboelectricity. More importantly, the two-dimensional sliding behavior of liquid droplets is comprehensively perceived by the e-skin and visually fed back in real-time on an indicator. Furthermore, the flow direction warning and intelligent closed-loop control of water leakage are also achieved by this e-skin, achieving the effect of human neuromodulation. This strategy compensates for the limitations of e-skin sensing droplets and greatly narrows the gap between artificial e-skins and human skins in perceiving functions.

Experimental development of lightweight manipulators with improved design cycle time that leverages off-the-shelf robotic arm components.

The growing market for lightweight robots inspires new use-cases, such as collaborative manipulators for human-centered automation. However, widespread adoption faces obstacles due to high R&D costs and longer design cycles, although rapid advances in mechatronic engineering have effectively narrowed the design space to affordable robot components, turning the development of lightweight robots into a component selection and integration challenge. Recognizing this transformation, we demonstrate a practical framework for designing lightweight industrial manipulators using a case-study of indigenously developed 5 Degrees-of-Freedom (DOF) cobot prototype. Our framework incorporates off-the-shelf sensors, actuators, gears, and links for Design for Manufacturing and Assembly (DFMA), along with complete virtual prototyping. The design cycle time is reduced by approximately 40% at the cost of cobot real-time performance deviating within 2.5% of the target metric. Our physical prototype, having repeatability of 0.05mm calculated as per the procedure defined in ISO 9283:1998, validates the cost-effective nature of the framework for creating lightweight manipulators, benefiting robotic startups, R&D organizations, and educational institutes without access to expensive in-house fabrication setups.

The effect of robot-assisted versus standard training on motor function following subacute rehabilitation after ischemic stroke - protocol for a randomised controlled trial nested in a prospective cohort (RoboRehab).

BACKGROUND: Body weight unloaded treadmill training has shown limited efficacy in further improving functional capacity after subacute rehabilitation of ischemic stroke patients. Dynamic robot assisted bodyweight unloading is a novel technology that may provide superior training stimuli and continued functional improvements in individuals with residual impairments in the chronic phase after the ischemic insult. The aim of the present study is to investigate the effect of dynamic robot-assisted versus standard training, initiated 6 months post-stroke, on motor function, physical function, fatigue, and quality of life in stroke-affected individuals still suffering from moderate-to-severe disabilities after subacute rehabilitation. METHODS: Stroke-affected individuals with moderate to severe disabilities will be recruited into a prospective cohort with measurements at 3-, 6-, 12- and 18-months post-stroke. A randomised controlled trial (RCT) will be nested in the prospective cohort with measurements pre-intervention (Pre), post-intervention (Post) and at follow-up 6 months following post-intervention testing. The present RCT will be conducted as a multicentre parallel-group superiority of intervention study with assessor-blinding and a stratified block randomisation design. Following pre-intervention testing, participants in the RCT study will be randomised into robot-assisted training (intervention) or standard training (active control). Participants in both groups will train 1:1 with a physiotherapist two times a week for 6 months (groups are matched for time allocated to training). The primary outcome is the between-group difference in change score of Fugl-Meyer Lower Extremity Assessment from pre-post intervention on the intention-to-treat population. A per-protocol analysis will be conducted analysing the differences in change scores of the participants demonstrating acceptable adherence. A priori sample size calculation allowing the detection of the minimally clinically important between-group difference of 6 points in the primary outcome (standard deviation 6 point, α = 5% and ß = 80%) resulted in 34 study participants. Allowing for dropout the study will include 40 participants in total. DISCUSSION: For stroke-affected individuals still suffering from moderate to severe disabilities following subacute standard rehabilitation, training interventions based on dynamic robot-assisted body weight unloading may facilitate an appropriate intensity, volume and task-specificity in training leading to superior functional recovery compared to training without the use of body weight unloading. TRIAL REGISTRATION: ClinicalTrials.gov. NCT06273475. TRIAL STATUS: Recruiting. Trial identifier: NCT06273475. Registry name: ClinicalTrials.gov. Date of registration on ClinicalTrials.gov: 22/02/2024.

Research on control strategy of pneumatic soft bionic robot based on improved CPG.

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot.

Origami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography.

Electrocorticography is an established neural interfacing technique wherein an array of electrodes enables large-area recording from the cortical surface. Electrocorticography is commonly used for seizure mapping however the implantation of large-area electrocorticography arrays is a highly invasive procedure, requiring a craniotomy larger than the implant area to place the device. In this work, flexible thin-film electrode arrays are combined with concepts from soft robotics, to realize a large-area electrocorticography device that can change shape via integrated fluidic actuators. We show that the 32-electrode device can be packaged using origami-inspired folding into a compressed state and implanted through a small burr-hole craniotomy, then expanded on the surface of the brain for large-area cortical coverage. The implantation, expansion, and recording functionality of the device is confirmed in-vitro and in porcine in-vivo models. The integration of shape actuation into neural implants provides a clinically viable pathway to realize large-area neural interfaces via minimally invasive surgical techniques.

Sensor-Enhanced Smart Gripper Development for Automated Meat Processing.

Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automation is spreading to increasingly complex fields of industry, smart tools with sensors and internal decision-making become necessities. CPS, such as robots and smart autonomous machinery, have been introduced in the meat industry in recent decades; however, the natural diversity of animals, potential anatomical disorders and soft, slippery animal tissues require the use of a wide range of sensors, software and intelligent tools. This paper presents the development of a smart robotic gripper for deployment in the meat industry. A comprehensive review of the available robotic grippers employed in the sector is presented along with the relevant recent research projects. Based on the identified needs, a new mechatronic design and early development process of the smart gripper is described. The integrated force sensing method based on strain measurement and magnetic encoders is described, including the adjacent laboratory and on-site tests. Furthermore, a combined slip detection system is presented, which relies on an optical flow-based image processing algorithm using the video feed of a built-in endoscopic camera. Basic user tests and application assessments are presented.

Investigation of the tradeoffs between tracking performance and energetics in heterogeneous variable recruitment fluidic artificial muscle bundles.

In traditional hydraulic robotics, actuators must be sized for the highest possible load, resulting in significant energy losses when operating in lower force regimes. Variable recruitment fluidic artificial muscle (FAM) bundles offer a novel bio-inspired solution to this problem. Divided into individual MUs, each with its own control valve, a variable recruitment FAM bundle uses a switching control scheme to selectively bring MUs online according to load demand. To date, every dynamic variable recruitment study in the literature has considered homogeneous bundles containing MUs of equal size. However, natural mammalian muscle MUs are heterogeneous and primarily operate based on Henneman's size principle, which states that MUs are recruited from smallest to largest for a given task. Is it better for a FAM variable recruitment bundle to operate according to this principle, or are there other recruitment orders that result in better performance? What are the appropriate criteria for switching between recruitment states for these different recruitment orders? This paper seeks to answer these questions by performing two case studies exploring different bundle MU size distributions, analyzing the tradeoffs between tracking performance and energetics, and determining how these tradeoffs are affected by different MU recruitment order and recruitment state transition thresholds. The only difference between the two test cases is the overall force capacity (i.e. total size) of the bundle. For each test case, a Pareto frontier for different MU size distributions, recruitment orders, and recruitment state transition thresholds is constructed. The results show that there is a complex relationship between overall bundle size, MU size distributions, recruitment orders, and recruitment state transition thresholds corresponding to the best tradeoffs change along the Pareto frontier. Overall, these two case studies validate the use of Henneman's Size Principle as a variable recruitment strategy, but also demonstrate that it should not be the only variable recruitment method considered. They also motivate the need for a more complex variable recruitment scheme that dynamically changes the recruitment state transition threshold and recruitment order based on loading conditions and known system states, along with a co-design problem that optimizes total bundle size and MU size distribution.

A review of robot-assisted ultrasound examination: Systems and technology.

BACKGROUND: At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will largely solve the shortage of medical resources. METHODS: According to the degree of automation, the handheld, semi-automatic and automatic ultrasound examination robot systems are summarised. Ultrasound scanning path planning and robot control are the keys to ensure that the robot systems can obtain high-quality images. Therefore, the ultrasound scanning path planning and control methods are summarised. The research progress and future trends are discussed. RESULTS: A variety of ultrasound robot systems have been applied to various medical works. With the continuous improvement of automation, the systems provide high-quality ultrasound images and image guidance for clinicians. CONCLUSION: Although the development of medical ultrasound robot still faces challenges, with the continuous progress of robot technology and communication technology, medical ultrasound robot will have great development potential and broad application space.

Added Value of a Robotic-assisted Bronchoscopy Platform in Cone Beam Computed Tomography-guided Bronchoscopy for the Diagnosis of Pulmonary Parenchymal Lesions.

BACKGROUND: Cone beam computed tomography (CBCT)-guided bronchoscopic sampling of peripheral pulmonary lesions (PPLs) is associated with superior diagnostic outcomes. However, the added value of a robotic-assisted bronchoscopy platform in CBCT-guided diagnostic procedures is unknown. METHODS: We performed a retrospective review of 100 consecutive PPLs sampled using conventional flexible bronchoscopy under CBCT guidance (FB-CBCT) and 100 consecutive PPLs sampled using an electromagnetic navigation-guided robotic-assisted bronchoscopy platform under CBCT guidance (RB-CBCT). Patient demographics, PPL features, procedural characteristics, and procedural outcomes were compared between the 2 cohorts. RESULTS: Patient and PPL characteristics were similar between the FB-CBCT and RB-CBCT cohorts, and there were no significant differences in diagnostic yield (88% vs. 90% for RB-CBCT, P=0.822) or incidence of complications between the 2 groups. As compared with FB-CBCT cases, RB-CBCT cases were significantly shorter (median 58 min vs. 92 min, P<0.0001) and used significantly less diagnostic radiation (median dose area product 5114 µGy•m2 vs. 8755 µGy•m2, P<0.0001). CONCLUSION: CBCT-guided bronchoscopy with or without a robotic-assisted bronchoscopy platform is a safe and effective method for sampling PPLs, although the integration of a robotic-assisted platform was associated with significantly shorter procedure times and significantly less radiation exposure.

Biofabrication of Living Actuators.

The impact of tissue engineering has extended beyond a traditional focus in medicine to the rapidly growing realm of biohybrid robotics. Leveraging living actuators as functional components in machines has been a central focus of this field, generating a range of compelling demonstrations of robots capable of muscle-powered swimming, walking, pumping, gripping, and even computation. In this review, we highlight key advances in fabricating tissue-scale cardiac and skeletal muscle actuators for a range of functional applications. We discuss areas for future growth including scalable manufacturing, integrated feedback control, and predictive modeling and also propose methods for ensuring inclusive and bioethics-focused pedagogy in this emerging discipline. We hope this review motivates the next generation of biomedical engineers to advance rational design and practical use of living machines for applications ranging from telesurgery to manufacturing to on- and off-world exploration.