Design of a Snake-like Robot for Rapid Injury Detection in Patients with Hemorrhagic Shock

Abstract

In the face of growing demand for emergency treatment in mass casualty incidents involving acute hemorrhagic shock, disaster sites often suffer from limited search and rescue manpower and inadequate medical detection capabilities. With the rapid development of robot technology, the deployment of robots provides greater flexibility and reliability in disaster emergency response and search and rescue work, which can effectively address the shortage of search and rescue forces and medical resources at disaster sites. This paper introduces a snake-like robot designed for the rapid triage of casualties with hemorrhagic shock. Through a structural design combining active wheels and orthogonal joints, the robot integrates the advantages of high-speed mobility of wheeled robots with the high flexibility of jointed robots so as to adapt to the complex environments typical of search and rescue scenarios. Meanwhile, the end of the robot is equipped with a visible light camera, an infrared camera and a voice interaction system, which realizes the rapid triage of casualties with hemorrhagic shock by collecting visible light, infrared and voice dialog data of the casualties. Through Webots software simulation and outdoor site simulation experiments, seven indicators of the designed snake-like search and rescue robot are verified, including walking speed, minimum passable hole size, climbing angle, obstacle-surmounting height, passable step size, ditch-crossing width and turning radius, as well as the effectiveness of collecting visible light images, infrared images and voice dialog data of the casualties.

1. Introduction

Hemorrhagic shock is the most common cause of death in mass casualty incidents such as earthquakes, tsunamis, fires, traffic accidents and wars. An analysis of 4596 battlefield deaths by the U.S. military showed that 87.3% of deaths occurred during pre-hospital treatment, of which 24.3% were considered potentially preventable. Among these potentially preventable deaths, 90.9% of the injuries were related to shock caused by severe blood loss without timely treatment [1]. In the 8.0-magnitude earthquake that struck Wenchuan, China, in 2008, 69,227 people were killed and 374,643 were injured. Among the injured, crush injuries accounted for 68%, with the three most common injury sites being the extremities (46.9%), head (14.7%) and chest (9.0%). Such injuries are highly likely to lead to hemorrhagic shock [2].

In mass casualty incidents involving sudden and large-scale casualties, there is often a prominent discrepancy between the limitations of medical resources, detection capabilities and data at disaster sites, and the accuracy required in mass triage [3]. The rapid advancement of robotic technology has enabled greater flexibility and reliability in the deployment of robots for disaster emergency response and search–rescue operations, which can effectively address the shortage of search–rescue forces at disaster sites [4,5].

As early as the 2005 Hurricane Katrina disaster in the United States, unmanned aerial vehicles and ground robots were deployed to search for victims in the ruins [6]. In 2011, underwater robots, drones, and ground robots were all involved in search and rescue, exploration, and inspection tasks during the Christchurch earthquake in New Zealand and the tsunami and nuclear leakage accidents caused by the Great East Japan Earthquake in the same year [7]. In 2013, the U.S. Defense Advanced Research Projects Agency (DARPA) launched the Robotics Challenge worldwide, with the theme of search and rescue robots [8]. In a semi-autonomous mode, robots overcome various simulated disaster scenes to carry out disaster relief, including high-difficulty tasks such as traversing complex terrain, opening and closing valves, and breaking doors to enter rooms. As shown in Figure 1, several typical search and rescue robots were developed, which can be mainly divided into tracked [9,10,11,12], wheeled [13,14], legged [15,16,17,18], and bionic [19,20] types. Tracked and wheeled robots have relatively fast movement speeds, can carry manipulators and heavy materials, and are more suitable for large-scale search and rescue operations in mines and intact buildings. Legged robots have excellent obstacle-surmounting capabilities and can perform search and rescue in relatively rugged environments. Bionic robots are highly flexible and have strong terrain adaptability, but they cannot carry large loads, making them more suitable for searching for people.

Snake-like robots are widely used in field operation fields due to their small size and flexible movement [21]. Yang applied snake-like robots to the inspection of high-voltage transmission lines, improving the real-time adaptability of snake-like robots in high-altitude movement [22]. Li proposed a compact self-assembling snake-like robot with joint drive and onboard visual perception, which enhances the perception and docking capabilities as well as driving performance of modular robots [23]. To meet the inspection needs of industrial and civil infrastructure, Leggieri [24] designed a mobile tracked snake-like robot, Canali [25] designed a long-arm cable-driven hyper-redundant snake-like robot, and Qin [26] completed the design method and dynamic modeling of a cable-driven snake-like manipulator maintainer. Aiming at addressing the problem of large noise in data collection during search and rescue using snake-like robots, Bao [27] studied the head stability control strategy of wheel-less snake-like robots based on inertial sensors, and Kim [28] adopted adaptive robust control schemes to enhance the stability of head images of snake-like robots. Chitikena [29] studied the ethical issues of snake-like robots in disaster search and rescue, and put forward the ethical and technical factors that must be considered in the research and development of snake-like robots.

In the event of mass casualty incidents, it is difficult for large-scale medical equipment and medical personnel to enter within a short period of time. Especially for injuries with high fatality rates such as hemorrhagic shock, a large number of medical staff are needed in a short time to conduct rapid triage of the injured so as to rationally allocate medical resources [30]. The use of bionic robots equipped with various portable sensors allows for rapid data collection from injured individuals, while artificial intelligence and medical big data technologies enable complete and swift triage of injuries. This has important practical significance for improving the survival rate of patients in casualty incidents.

This paper presents a snake-like robot designed for the rapid triage of casualties with hemorrhagic shock. The robot body features a structure combining active wheels and orthogonal joints, which enables it to integrate the advantages of the high-speed mobility of wheeled robots and the exceptional flexibility of jointed robots, so as to adapt to the complex terrain environments of the application scenarios. Meanwhile, the end of the robot is equipped with a visible light camera, an infrared camera and a voice interaction system. It realizes the rapid triage of casualties involving hemorrhagic shock by collecting the images, body temperature and voice dialog data of the injured. The innovation of this paper lies in its application scenario. Different from general search and rescue robots, this paper focuses on the specific scenario of rapid triage for hemorrhagic shock in disaster sites. This paper uses robot and artificial intelligence technologies to replace manual work in preliminary triage. It transforms the triage process from relying on on-site assessment by medical staff to technology-assisted rapid classification, thereby providing a basis for the accurate allocation of subsequent medical resources.

2. Design of Snake-like Robot System

2.1. Structural Design of Snake-like Robot

To be effectively deployed at disaster search and rescue sites, the robot’s body structure must be designed to have excellent spatial obstacle-surmounting capabilities and the ability to navigate through narrow spaces. A snake-like robot is a multi-degree-of-freedom chain-type robot composed of multiple similar joint modules connected in sequence. The orthogonal joint connection mode allows the adjacent joints of the snake-like robot to be connected via a revolute pair, and the axes of two adjacent revolute pairs are in an orthogonal relationship and perpendicular to the longitudinal axis of the snake’s body, endowing the snake-like robot with excellent 3D movement capabilities. In addition, by flexibly increasing or decreasing the number of orthogonal joints, the length and turning radius of the snake-like robot’s body can be adjusted, thereby balancing the robot’s spatial obstacle-surmounting capabilities with the ability to navigate through narrow spaces.

Figure 2 shows the snake-like robot designed in this study. The robot body consists of six orthogonal axis joints connected in series and four sets of active wheels. The skeleton components are arranged in orthogonal connection, with driven wheels mounted on them. Each section of the orthogonal component is connected with a semi-enclosed cabin, which is used to place components such as batteries and steering gear drivers, and the active wheel structure is arranged on the side of the cabin.

The degree of the robot’s abilities to surmount spatial obstacles and navigate through narrow spaces can be adjusted by increasing or decreasing the number of orthogonal joints and active wheels. Increasing the number of robot modules can extend the length of the robot body, thereby enhancing its spatial obstacle-surmounting capability. Reducing the number of robot modules can decrease the turning radius of the robot, thus improving its flexibility in navigating through narrow spaces.

To collect data on the casualties involving hemorrhagic shock, an information acquisition device consisting of a visible light camera, an infrared camera and a voice interaction system is installed at the end of the snake-like robot. The information acquisition device is connected to the snake’s body via a connecting rod bracket. By controlling the steering gear at the end of the bracket, the pitch and yaw angles of the cameras can be adjusted, thereby expanding the field of view for information collection.

The workspace of this snake-like robot breaks through the limitations of the 2D plane, expanding the robot’s activity range and operational flexibility. Additionally, based on the modular design integrating orthogonal joint connections and active wheels, it achieves 3D movement within its workspace, high-speed traversal across flat terrain, planar steering and detouring, and the ability to cross complex terrains such as those with obstacles and gaps. The components of the snake-like robot are mainly made of resin materials through 3D printing, which have low shrinkage and excellent yellowing resistance. The performance parameters of the resin material are shown in

Table 1. The performance parameters of the resin material.

Items	Material Standards	Parameters
Heat distortion temperature (0.46 MPa)	ASTM Method D648 [31]	44~57 °C
Hardness (Shore D)	ASTM Method D2240 [32]	76~86 Shore D
Tensile modulus	ASTM Method D638M [33]	2559~2678 MPa
Tensile strength		38~56 MPa
Elongation at break		8~14%
Flexural strength	ASTM Method D790M [34]	69~73 MPa
Flexural modulus		2670~2758 MPa
Notched impact strength	ASTM Method D256A [35]	36~60 J/m
Coefficient of thermal expansion	TMA (T < Tg)	90~103 × 10−6/°C
Poisson’s ratio	ASTM Method D638M	0.4~0.44
Dielectric constant at 60 Hz	ASTM Method D150-98 [36]	4.2~5.0
Dielectric constant at 1 KHz		3.3~4.2
Dielectric constant at 1 MHz		3.2~4.0
Insulating strength	ASTM Method D149-97a [37]	12.8~16.1 kV/mm

below.

2.2. Analysis of Motion Control of Snake-like Robot

The proposed body structure, which integrates active wheels with orthogonal joints, enables the snake-like robot to combine the advantages of both wheeled robots and multi-jointed robots. On flat terrain, the active wheels provide high-speed mobility, while on rugged surfaces, the robot enhances its three-dimensional obstacle-crossing capability through adaptive undulatory movements facilitated by the orthogonal joints. The mathematical model governing the serpentine motion of the robot is expressed in Equation (1):

$$\left\{\begin{array}{c}{\theta }_t(t)=\left({\displaystyle \frac{e^{\eta t}-1}{e^{\eta t}+1}}\right)\alpha \sin (\omega t+(i-1)\beta )\\ {\psi }_i(t)=0\end{array}\right.$$

(1)

In Formula (1), ${\theta }_t(t)$ is the angle of the i-th yaw joint of the robot at time t; ${\psi }_i(t)$ is the angle of the i-th pitch joint of the robot at time t; $\alpha ,\omega ,\beta$ are parameters of the wavy motion trajectory; and $\eta$ is the optimal parameter for robot motion.

The turning motion control function of the snake-like robot is shown in Equation (2):

$$\left\{\begin{array}{c}{\theta }_t(t)=\left({\displaystyle \frac{e^{\eta t}-1}{e^{\eta t}+1}}\right)(\alpha \sin (\omega t+(i-1)\beta ))+\gamma \\ {\psi }_i(t)=0\end{array}\right.$$

(2)

In Formula (2), ${\theta }_t(t)$ is the angle of the i-th yaw joint of the robot at time t; ${\psi }_i(t)$ is the angle of i-th pitch joint of the robot at time t; $\alpha ,\omega ,\beta ,\gamma$ are turning motion parameters; and $\eta$ is the optimal parameter for robot motion.

The control method for the lifting motion of the snake-like robot is to directly lift n of its joints. Enabling the lifting of the head joints of the snake-like robot can greatly expand the field of view and improve the practical performance of the robot. The lifting motion of the front joints has practical research significance for the snake-like robot to enter the photographing working mode. The rotation curve planning of each pitching joint during the lifting motion is shown in Equation (3):

$$\left\{\begin{array}{l}{\phi }_{Yi}(t)=A_{i}sin(\omega t)+B_i\\ {\phi }_{Pi}(t)=0\end{array}\right.$$

(3)

In Formula (3), ${\phi }_{Yi}(t)$ and ${\phi }_{Pi}(t)$ are the rotation values of the first pitch joint; $A_i$ is the waving motion amplitude parameter; and $B_i$ is the adjusted parameters around the rotation center.

The inverse kinematics of the snake-like robot can be solved via the geometric method. According to the analysis of head motion control, the head pitching motion of the snake-like robot can be regarded as a two-link mechanism, taking the right-side pose in Figure 3 as an example.

Since the actual lengths of the link mechanisms in the snake’s head are almost equal, they are assumed to be an isosceles two-link mechanism for the convenience of calculation. In triangle OAB, according to the cosine theorem, it can be obtained that

$$\cos \psi ={\displaystyle \frac{\sqrt{x^2+y^2}}{2l}}$$

(4)

According to the Pythagorean theorem, it can be derived that

$$\beta =\arctan 2{\displaystyle \frac{y}{x}}$$

(5)

Since the actual rotation angle of the first axis of the two-link mechanism is ${\theta }_1=\psi +\beta$, the formula for the rotation angle of axis 1 is as follows:

$${\theta }_1=\arccos {\displaystyle \frac{\sqrt{x^2+y^2}}{2l}}+\arctan 2{\displaystyle \frac{y}{x}}$$

(6)

Since this mechanism is an isosceles two-link mechanism, the angle of ${\theta }_2$ can be regarded as $2\psi$. Therefore, the formula for the rotation angle of axis 2 is as follows:

$${\theta }_2=2\arccos {\displaystyle \frac{\sqrt{x^2+y^2}}{2l}}$$

(7)

Compared with the DH method, the calculation of the robot’s inverse solution using the geometric method is simpler and more intuitive. By adjusting the angles of the two links, the information acquisition module can be adjusted at different angles.

2.3. Design of the Electrical System Structure of the Snake-like Robot

The control system of the snake-like robot is shown in Figure 4, which mainly consists of three parts: a human–computer interaction module, a perception module and a motion control module. Each module is connected to a Raspberry Pi 4B control board. The human–computer interaction module has two working modes: One uses a remote control handle based on 2.4 G wireless technology as the remote controller of the snake-like robot, with a stable remote control distance of about 25 m. The imaging information from the visible light camera is obtained through the Raspberry Pi remote desktop, allowing the operator to perform operations such as moving forward, backward, turning left, turning right and surmounting obstacles using the handle. The other mode is a human–computer interaction through information transmission via WIFI, using a web service deployed in the Raspberry Pi. The remote control handle can be used for controlling the snake-like robot at close range; when the snake-like robot works at a long distance or outside the line of sight, remote control can be performed through the web interface.

The perception module is installed at the tail of the snake-like robot and mainly consists of a visible light camera, a thermal imaging camera and a voice interaction system. The visible light camera is mainly used for visual feedback to the remote operator and capturing the physical condition of casualties with hemorrhagic shock, connected via a USB interface. The infrared camera is mainly used to assist in searching for casualties with hemorrhagic shock and obtaining their body temperature, connected to the Raspberry Pi through a USB-to-serial port. The voice interaction system is mainly used for real-time voice communication between the operator and the casualties. The snake-like robot is equipped with a speaker module and a sound-receiving module, connected via a USB interface. The remote operator can communicate with the casualties through a paired Bluetooth headset, and the voice responses of the casualties can be saved for analyzing their injury conditions.

The steering gear drive and control module is mainly used to control the active wheel steering gears and orthogonal joint steering gears of the snake-like robot. To reduce the number of cables in the robot, all steering gears adopt bus steering gears, which are connected to the Raspberry Pi through a USB-to-serial port. A total of 14 steering gears are used for the active wheels and orthogonal joints, which can be connected in series with only one serial cable. Compared with traditional PWM steering gears, this saves the internal wiring space of the robot, improves the stability of steering gear connections and enables feedback and protection control of the steering gear’s current, position and speed. The active wheel bus steering gears use TBS-K20 metal digital steering gears, which work in speed motion mode and can rotate infinitely. The orthogonal joints of the snake-like robot use ZP30D serial bus steering gears as drivers, working in position control mode to adjust the 3D posture of the robot.

3. Experiments and Analysis

3.1. Experiment on Motion Performance of Snake-like Robot

3.1.1. Simulation and Analysis of Snake-like Robot

According to Equation (1), α = 0.5 rad, ω = 2 rad/s, β = 1 rad, and the optimized parameter η = 2 are considered. The changes in each joint angle are shown in Figure 5, and the simulation results in Webots with version R2022a are shown in Figure 6.

According to Equation (2), the control parameters are α = 0.5 rad, ω = 2 rad/s, β = 1 rad, η = 2, with the following values set: γ = 0.5 rad and γ = −0.5 rad. The angular changes in each yaw joint are shown in Figure 7. The simulation results in Webots software are shown in Figure 8 and Figure 9.

The simulation results demonstrate that by adjusting the undulatory and turning motion parameters of the robot, we can effectively modulate three key characteristics of the snake-like robot’s locomotion: the lateral oscillation amplitude, forward velocity and turning radius. Furthermore, when combined with the coordinated control of the active wheels, this approach significantly enhances the robot’s mobility on rugged terrain, achieving both faster movement speeds and reduced turning radii. The main code for the snake-like robot simulation and the outdoor test video can be found in Supplementary Materials.

3.1.2. Outdoor Grassland Experiments and Analysis

Outdoor grassland experiments are shown in Figure 10. Most of the plants in the grassland are gramineous herbs. The grass leaves take root in the soil, making the contact surface relatively soft, which requires the active wheels of the snake-like robot to have good grip. The experimental results show that the soft ground induces a certain resistance to the robot’s active wheels that requires additional power and effort to be overcome. In addition, plants in the grassland may also become entangled in the robot’s components, increasing the maintenance and cleaning work of the robot.

3.1.3. Outdoor Experiment and Analysis on Gravel Ground

In disaster sites, there are many complex environments with sandy and gravel terrain. An irregular cobblestone river course was selected as the experimental site, as shown in Figure 11. Thanks to the combined movement of the active wheels and orthogonal joints, the snake-like robot is provided with strong power. Moreover, the deformation of the orthogonal joints enables the snake-like robot to effectively conform to the contour changes in the sandy and gravel river course, allowing it to move relatively smoothly in such an environment. Its flexibility and adaptability enable the snake-like robot to find a suitable body posture in sandy and gravel terrain, so as to pass through narrow passages, climb inclined surfaces and cross irregular obstacles.

3.1.4. Experiment and Analysis on Surmounting Step-Type Obstacles

In disaster situations, people can be easily trapped in buildings where there are often obstacles of varying heights such as steps. In this experiment, a step with a height of 30 cm was selected, as shown in Figure 12. The snake-like robot can successfully surmount the step of this height through posture adjustment. The snake-like robot flexibly adjusts its body posture, lifting and twisting its body to adapt to the height and shape of the step. Through such postural adjustments, the robot successfully overcomes the height difference in the step and smoothly crosses the obstacle.

3.1.5. Experiment and Analysis on Gap Crossing

In disaster scenarios such as earthquakes and explosions, there are often terrains with relatively wide gaps. We tested the robot’s ability to cross gaps independently without external assistance. For the gap-crossing test, a 35 cm wide gap was set up, as shown in Figure 13. By adjusting its body posture and movement mode to adapt to the width and shape of the gap, the snake-like robot flexibly stretched and contracted its body, successfully crossing the gap.

Seven indicators were set for the snake-like robot test: walking speed, minimum passable hole size, climbing angle, obstacle-surmounting height, passable step size, ditch-crossing width, and turning radius. The results of the motion experiment data are shown in

Table 2. Motion implementation indicators and experimental data results.

Items	Design Indicators	Experimental Conditions
Walking speed	≮0.2 m/s	0.28 m/s
Minimum passable hole	0.25 m × 0.25 m	0.15 m × 0.15 m
Climbing angle	≮30°	40°
Obstacle crossing height	≮0.25 m	0.35 m
Climbable step size	Height ≮ 0.175 m Width 0.26 m	Height 0.3 m Width 0.26 m
Gully crossing width	≮0.2 m	Max 0.5 m
Turning radius	≮0.25 m	0.2 m

, demonstrating that the robot’s maximum linear movement is 0.28 m/s, and that it can pass through a hole as small as 0.15 m × 0.15 m, climb a slope of 40 degrees, surmount obstacles with a vertical height of 0.35 m, and climb steps 0.3 m high and 0.26 m wide. In terms of ditch-crossing width, the robot can cross ditches with a maximum width of 0.5 m, and regarding the turning radius, the robot’s turning radius is 0.25 m. These data meet the design indicators.

3.2. Non-Contact Sensing Information Acquisition Experiment

3.2.1. Voice Information Acquisition and Analysis

The head of the snake-like robot is equipped with a microphone and a loudspeaker, allowing the operator to communicate remotely with the wounded via a head-mounted headset. After locating the wounded, to meet the needs of triaging hemorrhagic shock casualties, a standard voice question-and-answer process would be performed, as demonstrated in Figure 14. This process sequentially involves inquiring about information such as whether the wounded can respond vocally, whether they can state their name, whether they can answer simple mathematical operation questions, and the volume of their responses. The entire dialog process is recorded and saved.

3.2.2. Camera and Infrared Vision Acquisition and Analysis

The head of the snake-like robot is equipped with a visible light camera and an infrared camera. Operators can monitor the surrounding environment of the snake-like robot by viewing the collected visible light and infrared images on a portable display within a specified range. This is carried out via visible light and infrared vision image acquisition along with the WEB-based remote control interface, where operators can remotely control the robot through the WEB interface and simultaneously save the image information of the wounded for the swift screening of injuries using the triage terminal software version 1.0.

Figure 15 shows the triage results for patients with hemorrhagic shock based on camera and infrared images. The two images on the left display the image captured with the RGB camera and the infrared camera. Different colors are used to indicate the severity of the condition in patients with hemorrhagic shock. Black indicates that the patient is in terminal shock, on the verge of death, and requires immediate emergency treatment. Red indicates that the patient is in decompensated shock, facing immediate life-threatening risks, and needs to be sent to the emergency room for further inspection. Yellow indicates that the patient does not require emergency treatment but needs monitoring. Green indicates that the patient is in a stable condition with well-compensated vital signs. Figure 16 shows the facial features and infrared image of a patient experiencing hemorrhagic shock in a hospital, classified as Yellow. A neural network model with the SBP variable removed method was developed for triage. For details on the triage algorithm, please refer to study [38], performed by our research group. The system uses the changes in color blocks to reflect the different levels of injury severity. After the diagnosis process is completed, the system generates a text file in CSV format to store the diagnosis results, together with the patient’s original data, in the designated patient folder for subsequent access and analysis.

3.2.3. Ethical and Risk Considerations of the Snake-like Robot

In scenarios with scarce medical resources, robots equipped with multimodal sensors (e.g., infrared cameras, voice interaction systems) and AI algorithms are used to detect hemorrhagic shock severity in patients. Treatment resources are then allocated under the “severity-first” principle, but this approach carries non-negligible ethical risks, with misdiagnosis from incorrect classification being particularly critical. The robot’s detection results depend on data quality and algorithm performance. In disaster sites, interferences such as dim lighting or dust can distort sensor-collected data, including patients’ facial features and vital signs. Moreover, algorithm training data with insufficient severe-case samples or geographic biases often lead to model judgment errors and subsequent misdiagnosis. Robot detection relies on standardized data collection logic, which struggles to identify patients’ individual differences. If the robot cannot dynamically adjust detection thresholds, it may cause systematic misdiagnosis. This misdiagnosis essentially reflects the technology’s neglect of individual medical equity and violates the core medical ethics principle of respecting patients’ individual differences. Applying robot technology to detect its severity requires balancing efficiency and ethics. Measures should include improving detection accuracy via multimodal data fusion and edge computing optimization, and establishing a dual verification mechanism of robot initial screening and critical-case medical staff review. Additionally, both incorporating diverse samples during algorithm development and clarifying responsibility boundaries for technology application serve to avoid ethical risks from technical limitations.

4. Conclusions

This paper presents a snake-like robot designed for the rapid triage of casualties with hemorrhagic shock. The robot’s structural design of combining active wheels and orthogonal joints enables the integration of the high-speed mobility of wheeled robots with the high flexibility of jointed robots, thus allowing it to adapt to the complex terrain environments of application scenarios. Experiments on grass- and gravel-covered terrain and on surmounting step-type obstacles were conducted to verify seven indicators of the snake-like robot: walking speed, minimum passable hole size, climbing angle, obstacle-surmounting height, passable step size, ditch-crossing width and turning radius. The end of the robot is equipped with a visible light camera, an infrared camera and a voice interaction system, which all together realize the rapid triage of casualties involving hemorrhagic shock by collecting visible light, infrared, and voice dialog data. In future research, we will focus on the risks and ethical issues involved in using snake-like robots for hemorrhagic shock triage, such as issues related to improving triage accuracy and the ethics of medical treatment.