A portable imaging systems and methods thereof

Abstract

The present invention relates to a portable imaging system for performing automated ultrasound examination of one or more body parts of a user. The system comprising a scanning assembly configured to position one or more ultrasound probes relative to the one or more body parts, one or more ultrasound probes configured to acquire ultrasound image data of the one or more body parts, a control module operatively coupled to the scanning assembly and the one or more ultrasound probes and an image processing module configured to process the acquired ultrasound image data. The control module is configured to control movement of the one or more ultrasound probes based on predetermined information relating to the one or more body parts. Further, the control module is configured to adjust a position and / or orientation of the one or more ultrasound probes during scanning based on feedback derived from the image processing module. Further, a method for automated ultrasound examination of one or more body parts of a user by using portable imaging system is provided.

Description

[0001] A PORTABLE IMAGING SYSTEMS AND METHODS THEREOF

[0002] Field of the Invention

[0003] [1] The present invention relates to electromechanical imaging systems and methods for automated medical imaging, and in particular to portable imaging systems using automated ultrasound probes.

[0004] [2] The invention has been developed primarily for use with patients for imaging their bodies by employing a fully autonomous, clinical-grade robotic ultrasound imaging system designed for regulated medical device markets and will be described hereinafter with reference to this application. It will, however, be appreciated that the invention is not limited to this particular field of use.

[0005] Background of the Invention

[0006] [3] Ultrasound scans are widely used in the medical field, serving as a key imaging tool. They are commonly employed in diagnosing conditions affecting the kidneys and gallbladder, such as stones and other anomalies. It is assumed that if people have the facility of getting themselves checked over short periods of time, at low cost and convenience, it is possible to detect pathological conditions at earlier stages. This would allow for “treatment in time” to save the lives of a large number of people. However, access to skilled sonologists remains a significant challenge, particularly in remote and resource-limited regions. The availability of trained professionals is limited, leading to delays in diagnosis and treatment. Additionally, conventional ultrasound systems require manual operation, demanding both expertise and precision to ensure accurate imaging. The reliance on human operators introduces variability in scan quality and repeatability, posing concerns for consistent and reliable imaging. These limitations create a need for alternative solutions that can enhance accessibility, accuracy, and efficiency in ultrasound imaging.

[0007] [4] To address these challenges, robotic ultrasound systems have been developed. These systems can acquire ultrasound images with greater efficiency and consistency, potentially reducing patient wait times and enhancing the overall quality and repeatability of scans.

[0008] [5] Existing solutions to address this issue also include portable ultrasound devices, tele-robotic ultrasound systems, and semi-automated robotic imaging systems. Portable ultrasound devices have improved accessibility by enabling point-of-care imaging, allowing healthcare workers to conduct ultrasound scans outside traditional clinical settings.

[0009] [6] Tele-robotic ultrasound imaging enables remote specialists to operate the device. Semi-automated robotic systems integrate robotic arms and artificial intelligence to aid in probe positioning and scanning, reducing the dependency on human expertise.

[0010] [7] However, these approaches still require operator intervention or external guidance. Currently, prior art systems are either manual or tele-robotic systems that require human intervention during imaging operations.

[0011] [8] Despite advancements, these existing solutions exhibit several limitations. Normally, people do not get themselves diagnosed for diseases or abnormalities until advanced-stage symptoms become evident. This issue is exacerbated by the supplydemand gap, where the number of expert sonologists available to diagnose a population is limited, and they can only perform a finite number of scans within a given timeframe. As humans, their speed and efficiency are limited and variable. The availability and speed of imaging services are primary concerns, as large populations cannot be effectively scanned repeatedly over extended periods.

[0012] [9] Portable ultrasound devices often suffer from inconsistent imaging quality due to operator variability, leading to sub-optimal scans that may require repetition. Tele-robotic ultrasound systems depend on stable internet connectivity and real-time communication, which may not be feasible in remote or low-resource environments. Semi-automated robotic systems still require partial human involvement, necessitating trained personnel for setup, calibration, and intervention during scanning. Furthermore, the high costs associated with advanced robotic solutions make them impractical for widespread deployment, particularly in underserved regions. These shortcomings indicate the need for a more autonomous, reliable, and cost-effective solution.

[0013]

[0010] Furthermore, prior art autonomous robotic systems require instrument-level physical precision during site deployment; technicians must ensure the operating chassis and camera gantries are perfectly levelled using external tools. Any mechanical skew or uneven flooring completely degrades the spatial coordinate mapping of the robotic arms. Semi-automated systems currently present in the art suffer from inherent computational latency during sudden biological anomalies. They also fail to account for "catastrophic forgetting" during continuous neural networktraining, and frequently lack explicit medical-grade cybersecurity frameworks and algorithmic provenance, exposing them to enablement and regulatory rejections.

[0014]

[0011] The present invention seeks to provide an imaging system and a method for imaging, which will overcome or substantially ameliorate at least some of the deficiencies of the prior art, or to at least provide an alternative.

[0015]

[0012] It is to be understood that, if any prior art information is referred to herein, such reference does not constitute an admission that the information forms part of the common general knowledge in the art, in Australia or any other country.

[0016] Summary of the Invention

[0017]

[0013] According to a first aspect of the present invention, a portable imaging system for performing automated ultrasound examination of one or more body parts of a user is provided. The system comprising a scanning assembly configured to position one or more ultrasound probes relative to the one or more body parts, one or more ultrasound probes configured to acquire ultrasound image data of the one or more body parts, a control module operatively coupled to the scanning assembly and the one or more ultrasound probes and an image processing module configured to process the acquired ultrasound image data. The control module is configured to control movement of the one or more ultrasound probes based on predetermined information relating to the one or more body parts. The control module is further configured to adjust a position and / or orientation of the one or more ultrasound probes during scanning based on feedback derived from the image processing module.

[0018]

[0014] Advantageously, the portable imaging system provides an integrated automated ultrasound platform in which the scanning assembly, control module, and image processing module operate in a coordinated manner to enable closed-loop probe positioning and imaging. By controlling movement of the one or more ultrasound probes based on predetermined information relating to the body parts and further adjusting probe position and / or orientation in response to feedback derived from processed ultrasound image data, the system improves positioning accuracy, maintains consistent probe contact, and enhances image acquisition quality. This integrated configuration reduces dependence on skilled operators, increases repeatability of examinations across different users and environments, and enables adaptive scanning of anatomical regions through continuous interaction between sensing, processing, and actuation components.

[0015] In an embodiment, the scanning assembly comprises one or more robotic arms configured to be coupled with the one or more ultrasound probes.

[0019]

[0016] In an embodiment, the one or more robotic arms have six or more degrees of freedom.

[0020]

[0017] In an embodiment, the one or more robotic arms further comprise a linear axis providing translational movement.

[0021]

[0018] In an embodiment, the scanning assembly further comprising one or more sensors configured to provide real-time feedback relating to force and / or contact between the one or more ultrasound probes and the one or more body parts.

[0022]

[0019] In an embodiment, the one or more sensors comprise a multi-axis force torque sensor.

[0023]

[0020] In an embodiment, the scanning assembly comprises an end-effector assembly including a compliant mechanism.

[0024]

[0021] In an embodiment, the scanning assembly comprises a vibration-isolated support structure.

[0025]

[0022] In an embodiment, the vibration-isolated support structure is configured to reduce transmission of mechanical vibrations from the scanning assembly to the one or more ultrasound probes.

[0026]

[0023] In an embodiment, the scanning assembly comprises a primary three-dimensional imaging device and an auxiliary three-dimensional imaging device arranged to reduce visual occlusion.

[0027]

[0024] In an embodiment, the portable imaging system further comprising a sensing module configured to obtain spatial information of the one or more body parts.

[0028]

[0025] In an embodiment, the sensing module comprises a three-dimensional imaging device configured to generate depth data or a three-dimensional model of the one or more body parts.

[0029]

[0026] In an embodiment, the sensing module is configured to determine an initial position and / or orientation of the ultrasound probes based on the spatial information.

[0030]

[0027] In an embodiment, the sensing module comprises proximity sensors configured to detect objects within a predefined distance.

[0031]

[0028] In an embodiment, the sensing module comprises one or more inertial measurement units configured to provide calibration data.

[0032]

[0029] In an embodiment, the sensing module comprises a plurality of inertial measurement units distributed across the scanning assembly, one or more roboticarms, and one or more ultrasound probes, configured to generate calibration data for compensating structural misalignment of the system.

[0033]

[0030] In an embodiment, each of the one or more ultrasound probes comprises an array of transducers configured to generate and receive ultrasonic signals.

[0034]

[0031] In an embodiment, the image processing module is configured to identify one or more anatomical features in the acquired ultrasound image data.

[0035]

[0032] In an embodiment, the image processing module is configured to determine whether image quality satisfies one or more predefined criteria.

[0036]

[0033] In an embodiment, the image processing module comprises a feature detection model and a control optimisation module.

[0037]

[0034] In an embodiment, the control optimisation module comprises a machine learning model.

[0038]

[0035] In an embodiment, the control module is configured to modify the position and / or orientation of the one or more ultrasound probes when the image quality does not satisfy the one or more predefined criteria.

[0039]

[0036] In an embodiment, the control module is configured to modify operation of the scanning assembly based on user compliance with the instructions.

[0040]

[0037] In an embodiment, the control module is configured to adjust the position and / or orientation of the one or more ultrasound probes based on the identified one or more anatomical features.

[0041]

[0038] In an embodiment, the portable imaging system further comprising an analysis module configured to identify one or more areas of interest in the one or more body parts based on the processed ultrasound image data.

[0042]

[0039] In an embodiment, the analysis module comprises a machine learning model trained to identify one or more areas of interest.

[0043]

[0040] In an embodiment, the control module is configured to update the position and / or orientation of the ultrasound probes using predetermined information and feedback derived from the processed ultrasound image data.

[0044]

[0041] In an embodiment, the control module is configured to operate the system in an autonomous scanning mode.

[0045]

[0042] In an embodiment, the control module is configured to adjust operation of the scanning assembly based on the calibration data to compensate for tilt or uneven deployment surfaces.

[0043] In an embodiment, the portable imaging system further comprising an interface module including a display configured to present imaging data and receive input from the user.

[0046]

[0044] In an embodiment, the portable imaging system further comprising a communication module configured to transmit imaging results and / or identified one or more areas of interest to one or more external devices.

[0047]

[0045] In an embodiment, the portable imaging system further comprising a support surface configured to support at least a portion of the one or more body parts during scanning.

[0048]

[0046] In an embodiment, the scanning assembly comprises two or more robotic arms configured to position and manipulate the two or more ultrasound probes.

[0049]

[0047] In an embodiment, the two or more robotic arms are configured to move relative to each other to cooperatively control the position and / or orientation of the two or more ultrasound probes.

[0050]

[0048] In an embodiment, at least one robotic arm is configured to stabilise the one or more body parts while another robotic arm positions the one or more ultrasound probes.

[0051]

[0049] In an embodiment, the control module is configured to coordinate movement of the two or more robotic arms based on predetermined information and feedback derived from the processed ultrasound image data.

[0052]

[0050] In an embodiment, the portable imaging system further comprising g a data management module configured to store imaging data.

[0053]

[0051] In an embodiment, the data management module comprises CAN, USB, and Ethernet interfaces.

[0054]

[0052] In an embodiment, the data management module is configured to execute a store-and-forward protocol.

[0055]

[0053] In an embodiment, the data management module comprises a timesynchronisation module.

[0056]

[0054] In an embodiment, the data management module is configured to encrypt and securely transmit data.

[0057]

[0055] In an embodiment, the data management module is configured to operate independently of continuous network connectivity.

[0058]

[0056] In an embodiment, the portable imaging system further comprising a safety control subsystem configured to interrupt operation based on predefined conditions.

[0057] In an embodiment, the portable imaging system further comprising a tool exchange subsystem.

[0059]

[0058] In an embodiment, the tool exchange subsystem comprises a passive coupling mechanism configured to detachably couple different end-effector assemblies without the use of active actuators.

[0060]

[0059] In an embodiment, the passive coupling mechanism comprises one or more alignment members and one or more latch members configured to secure the endeffector assembly.

[0061]

[0060] In an embodiment, the alignment members comprise a plurality of pins configured to engage corresponding alignment channels.

[0062]

[0061] In an embodiment, the passive coupling mechanism is configured to engage or disengage in response to a rotational movement of a robotic arm.

[0063]

[0062] In an embodiment, the compliant mechanism of the end-effector assembly comprises one or more resilient members configured to provide controlled displacement under load.

[0064]

[0063] In an embodiment, the compliant mechanism further comprising one or more guide elements configured to constrain movement of the end-effector assembly along a predefined axis.

[0065]

[0064] In an embodiment, the compliant mechanism is configured to provide a predefined force threshold before displacement occurs.

[0066]

[0065] In an embodiment, the portable imaging system further comprising a power subsystem configured to provide backup power.

[0067]

[0066] In an embodiment, the portable imaging system further comprising a predictive maintenance module configured to monitor operational parameters of the scanning assembly.

[0068]

[0067] In an embodiment, the predictive maintenance module comprises a machine learning model configured to detect deviations in operational parameters.

[0069]

[0068] In an embodiment, the portable imaging system further comprising an audio interface configured to provide instructions to a user during scanning.

[0070]

[0069] In an embodiment, the portable imaging system further comprising a fluid dispensing device which is configured to apply a coupling medium to the one or more body parts.

[0071]

[0070] In an embodiment, the portable imaging system further comprising a cleaning subsystem configured to clean the one or more body parts after scanning.

[0071] In an embodiment, the cleaning subsystem comprises a cleaning end-effector configured to remove residual coupling medium.

[0072]

[0072] In an embodiment, the portable imaging system further comprising a wheeled chassis.

[0073]

[0073] According to a second aspect of the present invention, a method for automated ultrasound examination of one or more body parts of a user by using portable imaging system is provided. The method comprising positioning one or more ultrasound probes relative to the one or more body parts, acquiring ultrasound image data of the one or more body parts, controlling movement of the one or more ultrasound probes based on predetermined information relating to the one or more body parts, processing the acquired ultrasound image data and adjusting a position and / or orientation of the one or more ultrasound probes during scanning based on feedback derived from the processed ultrasound image data.

[0074]

[0074] Advantageously, the method enables a closed-loop automated ultrasound examination process in which probe positioning, image acquisition, data processing, and motion control are continuously integrated, thereby reducing reliance on manual operator input. By controlling movement of the one or more ultrasound probes based on predetermined information relating to the body parts and dynamically adjusting probe position and / or orientation using feedback derived from processed ultrasound image data, the method improves positional accuracy, consistency of probe contact, and overall image quality. This coordinated interaction between sensing, processing, and actuation subsystems enhances repeatability of scans across different users and deployment conditions, while enabling adaptive scanning of anatomical regions without requiring continuous human intervention.

[0075]

[0075] In an embodiment, the step of positioning the one or more ultrasound probes comprises using one or more robotic arms having six or more degrees of freedom.

[0076]

[0076] In an embodiment, the step of positioning further comprising a step of moving the one or more ultrasound probes along a linear axis.

[0077]

[0077] In an embodiment, the method further comprising a step of sensing force and / or contact between the one or more ultrasound probes and the one or more body parts.

[0078]

[0078] In an embodiment, the step of sensing comprises using a multi-axis force torque sensor.

[0079]

[0079] In an embodiment, the method further comprising a step of obtaining spatial information of the one or more body parts.

[0080] In an embodiment, the step of obtaining spatial information comprises generating a three-dimensional model or depth data.

[0080]

[0081] In an embodiment, the method further comprising a step of determining an initial position and / or orientation of the one or more ultrasound probes based on the spatial information.

[0081]

[0082] In an embodiment, the step of processing comprises identifying one or more anatomical features.

[0082]

[0083] In an embodiment, the method further comprising a step of adjusting the position and / or orientation of the one or more ultrasound probes based on the identified features.

[0083]

[0084] In an embodiment, the step of processing comprises determining whether image quality satisfies one or more predefined criteria.

[0084]

[0085] In an embodiment, the method further comprising a step of modifying the position and / or orientation of the one or more ultrasound probes when the criteria are not satisfied.

[0085]

[0086] In an embodiment, the method further comprising a step of obtaining calibration data using one or more inertial measurement units.

[0086]

[0087] In an embodiment, the method further comprising a step of compensating for structural misalignment of the portable imaging system based on the calibration data.

[0087]

[0088] In an embodiment, the method further comprising a step of coordinating movement of two or more robotic arms to perform a scanning operation.

[0088]

[0089] In an embodiment, the method further comprising a step of applying a coupling medium to the one or more body parts prior to acquiring ultrasound image data.

[0089]

[0090] In an embodiment, the method further comprising a step of synchronising ultrasound image data with sensor data.

[0090]

[0091] In an embodiment, the method further comprising a step of storing ultrasound image data and transmitting the stored data upon re-establishment of network connectivity.

[0091]

[0092] In an embodiment, the method further comprising a step of monitoring operational parameters of the portable imaging system to detect deviations.

[0092]

[0093] In an embodiment, the method further comprising a step of predicting maintenance requirements based on the detected deviations.

[0094] In an embodiment, the method further comprising a step of performing a cleaning operation on the one or more body parts after acquiring ultrasound image data.

[0093]

[0095] According to a third aspect of the present invention, a fully autonomous clinical ultrasound imaging system is provided. The system comprising a structural platform configured as a van-transportable mobile kiosk, a localized structural chassis enclosing a dedicated active cooling system and a localized edge-processing data management module, connected via internal CAN Bus, USB 3.1 , and Gigabit Ethernet pipelines, configured to execute a store-and-forward synchronization protocol to push operational data to a monitoring cloud server upon the re-establishment of network connectivity, a local historian module utilizing a hardware-level system clock pulsing at 30 Hz to time-synchronize multimodal data streams into a concatenated input tensor, a collaborative dual-robotic manipulation assembly, a multi-modal vision suite for generating occlusion-resistant volumetric depth maps, a distributed Inertial Measurement Unit (IMU) network configured to mathematically correct mechanical skews and spatial disbalance without instrument-level physical leveling, a multi-modal closed-loop sensory network for collision detection comprising a redundant network of inductive and capacitive sensors operating at a 50 mm threshold, a 6-axis force torque sensor mounted exclusively on a final joint for mechanical admittance control, a safety controller configured to arrest kinetic motion if non-final joint current draw exceeds 15% for more than 50 milliseconds, and a dynamic end-effector exchange subsystem comprising a passive chassis docking station.

[0094]

[0096] Advantageously, the fully autonomous clinical ultrasound imaging system overcomes the limitations of prior art systems by integrating all computational, sensing, and actuation components within a van-transportable mobile kiosk platform. The use of a localized edge-processing architecture, interconnected through highspeed Gigabit Ethernet, USB 3.1 , and CAN Bus pipelines, enables real-time data processing without reliance on continuous network connectivity, while a store-and-forward protocol ensures secure transmission of operational data upon reestablishment of connectivity. The inclusion of a dedicated active cooling system maintains optimal thermal conditions for sustained high-performance computation. Furthermore, the Local Historian, governed by a hardware-level system clock, ensures precise time-synchronisation of multimodal data streams into a unified input tensor. The distributed IMU network allows automatic compensation of mechanical skew andspatial misalignment without requiring instrument-level physical calibration, significantly improving ease of deployment. In addition, system safety and reliability are enhanced through a multi-modal closed-loop sensory network comprising redundant inductive and capacitive sensors for collision detection, and a safety controller configured to rapidly arrest motion under abnormal current conditions. Collectively, these features provide a robust, high-availability, and autonomous imaging platform capable of consistent operation in diverse and resource-constrained environments.

[0095]

[0097] In an embodiment, the multi-modal vision suite further comprises a kinetic isolation gantry configured as an L-shaped top-mounted frame that is vibration-isolated from the chassis, a central dome PTZ camera, a primary 3D spatial camera mounted directly above the calculated center of gravity, and an auxiliary 3D spatial camera to mitigate spatial occlusion.

[0096]

[0098] In an embodiment, the calibration module continuously evaluates IMU telemetry and automatically engages a hardware safety interlock if structural tilt exceeds a predefined threshold, locking the system in standby.

[0097]

[0099] In an embodiment, the system further comprising a hybrid active-passive compliant end-effector assembly serving as a probe shock absorber, comprising two rigid vertical guides featuring roller bearings on pins inserted into a vertical guide cavity, and utilizing three compression springs mathematically pre-compressed to establish a rigid breakaway force threshold. Preferably, each compression spring is geometrically constrained such that its free length divided by its mean diameter yields a slenderness ratio no greater than four (L / D < 4), rendering the springs inherently resistant to lateral buckling independent of internal guide rails.

[0098]

[0100] In an embodiment, the dynamic end-effector exchange subsystem utilises a passive mechanical tool changer featuring four precision-hardened index pins that mate with four reamed alignment channels, and inverse-profile latches configured to mechanically retract an internal center plate via a 15-degree anti-clockwise robotic rotation inside the docking station located exclusively at the distal lateral extremities of a horizontal translational 7th-axis unit, without the use of active pneumatic or electromagnetic components.

[0099]

[0101] In an embodiment, the ultrasonic probes further comprise a wired configuration bypassing slip rings via shielded internal ducts, and a wireless configuration utilizingan isolated shielded enclosure for onboard high-frequency RF signal processing operating via high-speed WiFi or Bluetooth protocols.

[0100]

[0102] In an embodiment, the system further comprising an autonomous clinical fluid dispenser featuring a 6-12 VDC micro peristaltic pump, a perpendicular microapproach Time-of-Flight (ToF) IR sensor array, active thermal regulation maintaining fluid at exactly 40 degrees Celsius, and a cleaner end-effector comprising an integrated electromagnet configured to magnetically retrieve a high-absorption sanitization towel from an automatically opening towel bin.

[0101]

[0103] In an embodiment, the system further comprising an autonomous hygiene and consumable replenishment subsystem comprising a sanitization sink with an internally connected system-operated hatch, integrated sterilization pans in the docking stations, and smart-refill dispensers utilizing umbilical docking ports.

[0102]

[0104] In an embodiment, the localized edge-processing module comprises a dualstage Al pipeline, an anchor-free CNN for ROI extraction configured to calculate a Minimizing Displacement Error (MDE) and a detection confidence level (C_det), a reinforcement learning (RL) agent for kinematic trajectory optimization configured to maximize a reward function positively correlated to C_det, and an inverse kinematics (IK) solver to translate spatial coordinates into joint motor commands.

[0103]

[0105] In an embodiment, the localized edge-processing module further comprises an active audio-verbal feedback interface to autonomously issue directed verbal commands to enforce patient physiological compliance.

[0104]

[0106] In an embodiment, the system further comprising a telerobotic training subsystem featuring an operator-facing haptic cancellation module configured to ingest 6-DoF spatial coordinates from an external haptic device or mobile application via network or Bluetooth protocols, transform said coordinates into force and direction vectors cycling at a 30 Hz frequency, and apply a low-pass kinematic filter to mathematically isolate and eliminate human operator tremor frequencies from incoming manual spatial commands.

[0105]

[0107] In an embodiment, the data management module executes a dual digital twin architecture comprising an operational space digital twin for spatial mapping and a patient monitoring digital twin aggregating historical telemetry for longitudinal analytics.

[0106]

[0108] In an embodiment, the data management module comprises an ESIM network gateway isolated during clinical scanning, configured to transmit anonymizedpredictive maintenance telemetry exclusively in asynchronous fallback mode utilizing TLS 1.3 cryptographic protocols, and wherein all localized data storage utilizes AES-256 encryption in compliance with IEC 81001-5-1 standards.

[0107]

[0109] In an embodiment, the system further comprising a clinically isolated power architecture utilizing a medical-grade UPS configured for a millisecond-latency switchover and onboard Lithium energy storage configured for continuous safe mechanical retraction during total power loss.

[0108]

[0110] According to a fourth aspect of the present invention, an automated method of acoustic data acquisition, trajectory control, and predictive maintenance utilising the fully autonomous clinical ultrasound imaging system, comprising executing primary calibration via IMU telemetry to correct structural skew and automatically resolving ongoing calibration drift utilizing an onboard software resolution module, coordinating a pre-scan preparation cycle wherein a first robotic arm attaches an ultrasound probe and a second robotic arm attaches a fluid dispenser to apply acoustic gel to a biological target mathematically identified via the operational space digital twin, generating volumetric depth maps via the kinetic isolation gantry, acquiring ultrasonic voxel data and comparing it against a learned normative 3D anatomical model locally on the edge-processing module, autonomously issuing directed verbal commands via the audio-verbal interface to ensure physiological compliance, calculating a Minimizing Displacement Error (MDE) alongside a detection confidence level (C_det) and translating spatial targets into joint motor commands via an inverse kinematics (IK) solver, generating an uncorrupted, annotated robotic ultrasound dataset within a telerobotic training subsystem by ingesting 6-DoF manual coordinates, translating said coordinates into force and direction vectors at a 30 Hz cycle synced via a hardwarelevel system clock to match the frame rate of the multi-modal vision suite, executing said vectors on the robotic arm within a 1 / 30 second time window, and saving the timestamped vectors, 3D digital twin frames, camera feeds, and reconstructed ultrasound images to a local historian, executing a post-scan autonomous hygiene cycle wherein the second robotic arm attaches an electromagnetic cleaner to physically wipe the biological target and discard waste into an automated bin, while the first robotic arm docks the ultrasound probe into a system-operated sanitization sink, flagging data packets for review while expressly omitting the generation of a deductive medical diagnosis, and processing continuous hardware health-check data,kinetic current-draw deviations, and end-effector telemetric inventory data through a predictive maintenance artificial intelligence model.

[0109]

[0111] Advantageously, the automated method enables fully autonomous ultrasound data acquisition and system operation by leveraging a collaborative dual-robotic manipulation assembly capable of executing coordinated pre-scan, scan, and postscan tasks without human intervention. The incorporation of a distributed IMU network across the trolley, robotic arms, and vision components enables continuous mathematical correction of structural skew and drift, thereby eliminating dependence on precision deployment conditions and ensuring consistent spatial accuracy in diverse environments. Further, the mounting of the multi-modal vision suite on a vibration-isolated, L-shaped kinetic isolation gantry preserves the integrity of volumetric depth mapping despite dynamic robotic motion. The method’s closed-loop control architecture, characterised by the computation of a Minimizing Displacement Error (MDE) in conjunction with a detection confidence level (C_det), allows real-time optimisation of probe positioning through inverse kinematics, thereby enhancing imaging reliability and repeatability. In addition, the utilisation of a dual digital twin architecture enables simultaneous real-time spatial mapping and longitudinal data aggregation, while the synchronised acquisition and storage of multimodal datasets via a hardware-clocked local historian ensures the generation of high-fidelity, temporally coherent training data. Collectively, these features result in a robust, and self-calibrating system that improves imaging consistency, reduces operator dependency, and facilitates continuous predictive maintenance and system learning without reliance on external infrastructure.

[0110]

[0112] In an embodiment, the reinforcement learning agent is structured as a computational tool utilizing a Deep Deterministic Policy Gradient (DDPG) algorithm governed by human-defined hyperparameters, and generated utilizing a rigorously documented dataset sourced from fully anonymized clinical repositories verified via Institutional Review Board (IRB) anonymization protocols.

[0111]

[0113] In an embodiment, the predictive maintenance artificial intelligence model utilizes an Elastic Weight Consolidation (EWC) module to mathematically protect synaptic weights associated with prior spatial navigation and hardware diagnostic tasks against catastrophic forgetting using a Fisher information matrix diagonal, mathematically governed by the penalty loss function: L(0) = L_new(0) + Z (A / 2) F_i (0_i - 0*_A,i)2.

[0114] This invention may also be said broadly to comprise in the parts, elements, and features referred to or indicated in the specification of the application, individually or collectively, and any or all combinations of any two or more of said parts, elements, or features, and where specific integers are mentioned herein which have known equivalents in the art to which this invention relates, such known equivalents are deemed to be incorporated herein as if individually set forth.

[0112]

[0115] To those skilled in the art to which the invention relates, many changes in construction and widely differing embodiments and applications of the invention will suggest themselves without departing from the scope of the invention as defined in the appended claims. The disclosures and the descriptions herein are purely illustrative and are not intended to be in any sense limiting.

[0113]

[0116] Other aspects of the invention are also disclosed.

[0114] Brief Description of the Drawings

[0115]

[0117] Notwithstanding any other forms which may fall within the scope of the present invention, a preferred embodiment of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:

[0116]

[0118] Fig. 1 illustrates a portable imaging system for performing automated ultrasound examination of one or more predetermined body parts of a person, in accordance with an embodiment of the present invention;

[0117]

[0119] Fig. 2 illustrates a method for performing automated ultrasound examination of one or more body parts of a person using the portable imaging system 100, in accordance with an embodiment of the present invention;

[0118]

[0120] Fig. 3 illustrates a system architecture of the fully autonomous clinical ultrasound imaging system in accordance with yet another embodiment of the present invention;

[0119]

[0121] Fig. 4A illustrates an orthographic perspective view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0120]

[0122] Fig. 4B illustrates a side elevation view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0121]

[0123] Fig. 4C illustrates a rear-side elevation view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0122]

[0124] Fig. 4D illustrates a side elevation view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0125] Fig. 4E illustrates a top plan view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0123]

[0126] Fig. 4F illustrates a bottom plan view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0124]

[0127] Fig. 4G illustrates a rear elevational view of the fully autonomous clinical robotic ultrasound imaging system of Fig. 3;

[0125]

[0128] Fig. 5 illustrates a hybrid active-passive compliant end-effector assembly in accordance with an embodiment of the present invention;

[0126]

[0129] Fig. 6 illustrates a passive dynamic end-effector exchange coupling in accordance with an embodiment of the present invention; and

[0127]

[0130] Fig. 7 illustrates an automated hygiene and consumable replenishment subsystem in accordance with an embodiment of the present invention.

[0128] Detailed Description of Embodiments

[0129]

[0131] It should be noted in the following description that like or the same reference numerals in different embodiments denote the same or similar features.

[0130]

[0132] The invention utilises localized edge-processing, a collaborative dual-robotic architecture comprising 6-DoF arms on a shared horizontal axis, an Inertial Measurement Unit (IMU) auto-calibration network, a vibration-isolated kinetic gantry, dynamic passive mechanical end-effector exchange at distal extremities, payload-calibrated hybrid active-passive compliant end-effectors, an active audio-verbal patient compliance interface, and an autonomous hygiene ecosystem. These components execute acoustic data acquisition, kinematic trajectory control, and hardware predictive maintenance without reliance on continuous cloud connectivity, continuous human intervention, or instrument-level deployment precision.

[0131]

[0133] Figure 1 illustrates a portable imaging system 100 for performing automated ultrasound examination of one or more predetermined body parts of a person, in accordance with an embodiment of the present invention. The system 100 is configured as an integrated electromechanical imaging platform comprising coordinated actuation, sensing, processing, control, and communication subsystems.

[0132]

[0134] The system 100 comprises a scanning assembly 101 configured to position one or more ultrasound probes 103 relative to the body parts. In preferred embodiments, the scanning assembly 101 comprises one or more robotic arms having six or more degrees of freedom and, optionally, a linear translational axis, enabling full spatial manipulation within a three-dimensional workspace.

[0135] In some embodiments, the scanning assembly 101 comprises two or more robotic arms configured to cooperatively control the position and / or orientation of the ultrasound probes 103, wherein at least one robotic arm stabilises a target region while another performs scanning. The control module 102 coordinates motion between the robotic arms to execute synchronised scanning trajectories.

[0133]

[0136] The one or more ultrasound probes 103 comprise transducer arrays configured to generate and receive ultrasonic signals for imaging internal anatomical structures. The probes 103 may further be associated with one or more sensors configured to provide real-time feedback relating to force and / or contact between the probe and the body. In some embodiments, the one or more sensors comprise a multi-axis forcetorque sensor configured to measure interaction forces and enable controlled mechanical admittance during probe contact.

[0134]

[0137] The scanning assembly 101 may further comprise an end-effector assembly including a compliant mechanism configured to provide controlled displacement under load. The compliant mechanism may include one or more resilient members and guide elements configured to constrain motion along a predefined axis and establish a predefined force threshold prior to displacement.

[0135]

[0138] The system 100 may further comprise a sensing module configured to obtain spatial information of the body parts. In some embodiments, the sensing module comprises one or more three-dimensional imaging devices configured to generate depth data or a three-dimensional model of the body. The sensing module may further comprise proximity sensors configured to detect objects within a predefined distance, and one or more inertial measurement units (IMUs) distributed across the scanning assembly 101 , robotic arms, and probes 103. The IMUs are configured to generate calibration data for compensating structural misalignment of the system 100 and correcting for tilt or uneven deployment surfaces without requiring manual leveling.

[0136]

[0139] The control module 102 is operatively coupled to the scanning assembly 101 and the ultrasound probes 103, and is configured to control movement based on predetermined information relating to the body parts. The control module 102 is further configured to update probe position and orientation using feedback derived from processed ultrasound image data and identified anatomical features, thereby enabling adaptive scanning.

[0140] In some embodiments, the control module 102 operates the system 100 in an autonomous scanning mode and adjusts operation based on calibration data to compensate for deployment conditions.

[0137]

[0141] The image processing module 104 is configured to process ultrasound image data acquired by the probes 103. The module may identify anatomical features and determine whether image quality satisfies predefined criteria. In some embodiments, the image processing module 104 comprises a feature detection model and a control optimisation module, wherein the control optimisation module comprises a machine learning model configured to assist in probe positioning and scanning optimisation.

[0138]

[0142] The analysis module 105 is configured to analyse processed ultrasound data to identify one or more areas of interest within the body parts. The analysis module 105 may comprise a machine learning model trained to detect anatomical features or regions requiring further examination.

[0139]

[0143] The communication module 106 is configured to transmit imaging data, processed outputs, and analysis results to one or more external devices and to receive input signals therefrom.

[0140]

[0144] In some embodiments, the system 100 further comprises a data management module configured to store imaging data and operate using communication interfaces including CAN, USB, and Ethernet protocols. The data management module may execute a store-and-forward protocol, operate independently of continuous network connectivity, and provide encrypted data transmission.

[0141]

[0145] The system 100 may further comprise a safety control subsystem configured to interrupt operation based on predefined conditions, including abnormal force interaction, positional deviation, or system fault.

[0142]

[0146] The system 100 may further comprise a tool exchange subsystem configured to detachably couple different end-effector assemblies. In some embodiments, the tool exchange subsystem comprises a passive coupling mechanism including alignment members and latch members configured to secure and release end-effectors in response to robotic motion.

[0143]

[0147] The system 100 may further comprise a power subsystem configured to provide backup power, ensuring continuous operation or safe shutdown during power interruption.

[0148] In some embodiments, the system 100 includes a predictive maintenance module configured to monitor operational parameters of the scanning assembly 101 and detect deviations using a machine learning model.

[0144]

[0149] The system 100 may further comprise an audio interface configured to provide instructions to a user during scanning.

[0145]

[0150] In some embodiments, the system 100 includes a fluid dispensing device configured to apply a coupling medium to the body parts prior to imaging, and a cleaning subsystem configured to remove residual coupling medium after scanning.

[0146]

[0151] The system 100 may further comprise a wheeled chassis enabling mobility and deployment across different clinical or remote environments.

[0147]

[0152] As shown in Figure 1, the scanning assembly 101 positions the ultrasound probes 103, which acquire imaging data processed by the image processing module 104. Feedback is provided to the control module 102, enabling continuous adjustment of probe positioning. The analysis module 105 evaluates the processed data, and the communication module 106 facilitates interaction with external systems.

[0148]

[0153] Figure 2 illustrates a method 200 for performing automated ultrasound examination of one or more body parts of a person using the portable imaging system 100, in accordance with an embodiment of the present invention.

[0149]

[0154] At step 202, the method comprises positioning one or more ultrasound probes 103 relative to one or more predetermined body parts of a person using the scanning assembly 101. The positioning is controlled by the control module 102, which generates motion commands for the scanning assembly 101 based on predetermined information relating to the one or more body parts. In some embodiments, such predetermined information includes spatial data obtained from a sensing module and calibration data derived from a distributed inertial measurement unit (IMU) network configured to compensate for structural misalignment.

[0150]

[0155] At step 204, the method comprises acquiring ultrasound image data of the one or more body parts using the one or more ultrasound probes 103. The ultrasound probes 103 are positioned in contact with the body parts by the scanning assembly 101 , and acquire ultrasonic data representative of internal anatomical structures. In some embodiments, force interaction between the ultrasound probes 103 and the body parts is monitored using one or more sensors associated with the scanning assembly 101.

[0156] At step 206, the method comprises controlling movement of the one or more ultrasound probes 103 using the control module 102, based on predetermined information relating to the one or more body parts. The control module 102 generates actuation commands for the scanning assembly 101 , including joint-space or Cartesian-space trajectories, and in some embodiments utilises an inverse kinematics (IK) solver to translate spatial targets into motion commands.

[0151]

[0157] In some embodiments, the control module 102 operates in conjunction with a control optimisation module comprising a machine learning model to optimise probe positioning during scanning.

[0152]

[0158] At step 208, the method 200 comprises processing the acquired ultrasound image data using the image processing module 104. The image processing module 104 is configured to identify one or more anatomical features and evaluate image quality based on predefined criteria. In some embodiments, the image processing module 104 comprises a feature detection model configured to extract regions of interest from the ultrasound image data.

[0153]

[0159] At step 210, the method 200 comprises adjusting a position and / or orientation of the one or more ultrasound probes 103 during scanning using the control module 102, based on feedback derived from the processed ultrasound image data. The image processing module 104 generates feedback signals which are transmitted to the control module 102, enabling dynamic adjustment of motion commands applied to the scanning assembly 101, thereby forming a closed-loop control system.

[0154]

[0160] In some embodiments, the method 200 further comprises analysing processed ultrasound image data using the analysis module 105 to identify one or more areas of interest within the body parts.

[0155]

[0161] The method 200 may further comprise transmitting ultrasound image data, processed data, or analysis results to one or more external devices using the communication module 106 and receiving input signals therefrom. The method 200 may further comprise obtaining spatial information relating to the body parts using a sensing module and generating calibration data using one or more inertial measurement units (IMUs) and compensating for structural misalignment of the system 100 based on the calibration data.

[0156]

[0162] In some embodiments, the method 200 further comprises applying a coupling medium to the one or more body parts prior to acquisition of ultrasound image data using a fluid dispensing device coupled to the scanning assembly 101.

[0163] The method 200 may further comprise storing ultrasound image data in a data management module and synchronising data using a hardware-level system clock and transmitting stored data using a store-and-forward protocol via the communication module 106.

[0157]

[0164] The method 200 may further comprise monitoring operational parameters of the scanning assembly 101 and detecting deviations using a predictive maintenance module comprising a machine learning model.

[0158]

[0165] The method 200 may further comprise cleaning the one or more body parts after acquisition of ultrasound image data using a cleaning subsystem coupled to the scanning assembly 101.

[0159]

[0166] Advantageously, the method 200 utilises the coordinated operation of the scanning assembly 101 , control module 102, ultrasound probes 103, image processing module 104, analysis module 105, and communication module 106 to provide a closed-loop, automated ultrasound imaging process with improved positional accuracy, repeatability, and reduced operator dependency.

[0160]

[0167] Figure 3 illustrates a system architecture of the fully autonomous clinical ultrasound imaging system 1000, in accordance with yet another embodiment of the present invention, configured as a van-transportable mobile platform integrating sensing, computation, robotic manipulation, and hygiene subsystems within a unified operational framework.

[0161]

[0168] The system 1000 comprises a localised edge-processing data management module configured to perform computational processing of multimodal data streams. The edge-processing module operates as a primary control and data fusion unit and includes one or more processors configured to execute perception, control, and optimisation functions. The edge-processing module comprises a dual-stage artificial intelligence pipeline. In a first stage, a perception module utilises an anchor-free convolutional neural network architecture, including a YOLOv8-derived implementation, configured to map the operational space and calculate a Minimizing Displacement Error (MDE) and a detection confidence level (C_det). In a second stage, a control optimisation module comprises a reinforcement learning agent, including a Deep Deterministic Policy Gradient (DDPG) algorithm, configured to generate kinematic trajectories based on outputs from the perception module. The edge-processing module further comprises an inverse kinematics (IK) solver configured to translate spatial coordinates into joint motor commands for actuation ofthe robotic assembly. The edge-processing module is operatively coupled to a telerobotic training subsystem configured to ingest six-degree-of-freedom (6-DoF) spatial coordinates from external input devices and transform said coordinates into force and direction vectors. The subsystem operates in synchronisation with a hardware-level system clock pulsing at 30 Hz, thereby aligning command execution with multimodal data streams.

[0162]

[0169] The system 1000 further comprises a digital twin architecture including an operational space digital twin configured for real-time spatial mapping and target identification, and a patient monitoring digital twin configured to aggregate longitudinal telemetry data for analysis.

[0163]

[0170] The system 1000 further comprises a local historian module configured to time-synchronise multimodal data streams into a concatenated input tensor using the hardware-level system clock. The local historian stores sensor data, imaging data, robotic state data, and control signals for subsequent retrieval and analysis.

[0164]

[0171] The system 1000 further comprises a predictive maintenance module configured to evaluate hardware health and detect kinetic current-draw deviations. In some embodiments, the predictive maintenance module utilises an Elastic Weight Consolidation (EWC) algorithm governed by a Fisher information matrix diagonal to protect previously learned parameters, in accordance with the penalty loss function:

[0165]

[0166]

[0172] The system 1000 further comprises a network interface including an ESIM gateway configured to execute a store-and-forward communication protocol, wherein operational data is transmitted to a remote monitoring server upon re-establishment of network connectivity. Local data storage utilises AES-256 encryption and network transmission is secured using TLS 1.3 protocols.

[0167]

[0173] The system 1000 further comprises a multi-modal vision suite configured to generate occlusion-resistant volumetric depth maps. The vision suite is mounted on a kinetic isolation gantry configured as an L-shaped, vibration-isolated structure. The vision suite comprises a central dome PTZ camera, a primary 3D spatial camera positioned substantially above a calculated centre of gravity of the system, and an auxiliary 3D spatial camera configured to mitigate spatial occlusion.

[0174] The system 1000 further comprises a collaborative dual-robotic manipulation assembly including a first robotic arm and a second robotic arm, each comprising multiple degrees of freedom. The robotic arms are mounted on a shared horizontal translational axis configured to enable coordinated lateral movement across a scanning region. Each robotic arm comprises a 6-axis force torque sensor mounted exclusively on a final joint to enable strict mechanical admittance control during interaction with a biological target.

[0168]

[0175] The system 1000 further comprises a closed-loop sensory and safety network including a distributed inertial measurement unit (IMU) network configured to mathematically correct structural skew and spatial disbalance without instrument-level physical leveling. The safety network further comprises a redundant network of inductive and capacitive sensors configured to detect proximity within a predefined threshold distance of approximately 50 mm. A safety controller is configured to arrest kinetic motion if non-final joint current draw exceeds 15% for more than 50 milliseconds.

[0169]

[0176] The system 1000 further comprises a clinically isolated power and thermal management infrastructure including a medical-grade uninterruptible power supply configured for millisecond-latency switchover and an onboard lithium energy storage system configured to enable continuous safe mechanical retraction during total power loss. A dedicated active cooling system is provided to maintain optimal computational operating temperatures.

[0170]

[0177] The system 1000 further comprises a dynamic end-effector exchange subsystem located at distal extremities of the horizontal translational axis. The subsystem comprises a passive mechanical tool changer utilising precision-hardened index pins and inverse-profile latches configured to enable end-effector attachment and detachment without active pneumatic or electromagnetic components.

[0171]

[0178] The system 1000 further comprises a hybrid active-passive compliant endeffector assembly configured as a probe shock absorber. The assembly comprises a rigid upper housing and a floating lower carriage coupled via compression springs and guided by vertical alignment structures. The assembly establishes a predefined breakaway force threshold in accordance with:

[0172]

[0173] where spring geometry is constrained such that a slenderness ratio satisfies:

[0174]

[0175] thereby preventing lateral buckling.

[0176]

[0179] The system 1000 further comprises an autonomous hygiene and consumable replenishment subsystem including a sanitisation sink with a system-operated hatch, smart-refill fluid dispensers, an electromagnetic cleaner end-effector, and automated towel and waste disposal units.

[0177]

[0180] The system 1000 further comprises a patient interface including an active audio-verbal feedback system configured to autonomously issue directed commands to enforce patient physiological compliance during scanning.

[0178]

[0181] As shown in Figure 3, the system 1000 integrates perception, control, and actuation subsystems to perform automated ultrasound imaging, wherein spatial mapping, robotic motion, and data acquisition are continuously coordinated in a closed-loop manner.

[0179]

[0182] Figure 4A illustrates an orthographic perspective view 1002 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3 configured as a van-transportable mobile kiosk, showing the integration of the collaborative dual-robotic manipulation assembly, multi-modal vision suite, user interface components, and structural chassis.

[0180]

[0183] The system 1000 is supported on a mobile chassis defined by a bottom structure 2111 , mounted on a plurality of castor wheels 2116, each provided with a locking mechanism 2110 to secure the system 1000 during operation. A push bar 2122 is provided to facilitate manual relocation of the system.

[0181]

[0184] The chassis further comprises removable structural panels including a front cover 2118, a removable front cover 2113, and a removable side cover 2108, providing access to internal subsystems including the localised edge-processing module, power infrastructure, and active cooling system. A filtered air intake 2115 is provided to maintain controlled airflow for thermal management.

[0182]

[0185] The system 1000 comprises a human-machine interface 2106 mounted on an articulated joint 2107, enabling adjustable positioning for operator interaction. The HMI 2106 provides access to system status, operational modes, and user inputs in accordance with the localised edge-processing architecture. An emergency stopbutton 2112 is positioned on the chassis to enable immediate interruption of system operation in response to safety conditions.

[0183]

[0186] The system 1000 comprises a multi-modal vision suite mounted on a vibration-isolated gantry structure. The gantry includes a vertical pillar 2103 and a joint assembly 2102 configured to mechanically isolate the vision sensors from vibrations induced by robotic motion.

[0184]

[0187] A surveillance PTZ camera 2101 is mounted on the gantry for monitoring and supervisory observation. A primary three-dimensional spatial camera 2123 is positioned to align with the calculated center of gravity of the operational workspace, and an auxiliary three-dimensional spatial camera 2125 is positioned to mitigate occlusion and provide redundant depth perception.

[0185]

[0188] The system 1000 comprises a collaborative dual-robotic manipulation assembly including a first robotic arm 2104 and a second robotic arm 2124, each configured as a multi-degree-of-freedom manipulator. The robotic arms are mounted on a shared horizontal translational axis 2117, enabling lateral movement across the patient workspace and coordinated execution of scanning, dispensing, and hygiene operations. Each robotic arm is configured to carry interchangeable end-effectors and to operate under closed-loop control using force feedback and perception data derived from the multi-modal vision suite and edge-processing module.

[0186]

[0189] The system 1000 comprises multiple docking stations located at distal regions of the translational axis. A docking station 2114 is configured for ultrasound probe endeffectors, and a separate docking station 2120 is configured for fluid dispensing and cleaning end-effectors. The docking stations are configured to interface with a passive mechanical tool exchange system, enabling automated attachment and detachment of end-effectors without active pneumatic or electromagnetic actuation.

[0187]

[0190] An ultrasound transducer probe 2119 is shown positioned for imaging, configured to be manipulated by one of the robotic arms for acquisition of ultrasound data.

[0188]

[0191] A fluid dispensing subsystem includes a gel dispenser nozzle 2121 , configured to apply acoustic coupling medium to the patient prior to scanning, in accordance with the autonomous pre-scan preparation workflow. The system 1000 includes cleaning solution refill points 2109, enabling replenishment of consumables used by the autonomous hygiene subsystem.

[0192] A docking pod visor 2105 is provided to shield and protect docking interfaces and end-effector exchange zones, ensuring controlled operation and contamination management.

[0189]

[0193] As shown in Figure 4A, the components collectively implement the integrated system 1000 described in Figure 3, wherein the robotic arms 2104, 2124 operate along the shared axis 2117, the vision suite mounted on the vibration-isolated gantry provides spatial perception, and the docking stations enable dynamic tool exchange to support scanning, fluid dispensing, and cleaning workflows.

[0190]

[0194] The structural chassis houses the localised edge-processing module, power infrastructure, and safety systems, while the HMI 2106 and emergency stop 2112 provide operator interaction and safety control.

[0191]

[0195] Advantageously, the configuration illustrated in Figure 4A provides a compact, mobile, and fully integrated clinical imaging platform in which robotic manipulation, multimodal sensing, and closed-loop subsystems are co-located within a single chassis, thereby enabling rapid deployment, stable operation, and reduced dependency on external infrastructure.

[0192]

[0196] Figure 4B illustrates a side elevation view 1004 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the spatial arrangement and mechanical integration of the collaborative dual-robotic manipulation assembly, multi-modal vision suite, end-effector systems, and chassis-mounted subsystems.

[0193]

[0197] The system 1000 comprises a multi-modal vision suite mounted on a vibration-isolated gantry structure, including an auxiliary three-dimensional spatial camera 2201 and a primary three-dimensional spatial camera 2219, each mounted on vibration-isolated joints to decouple sensing elements from mechanical vibrations induced by robotic motion. A surveillance PTZ camera 2220 is positioned on the gantry to provide continuous visual monitoring of the operational environment. The vision suite is configured to generate volumetric depth maps and spatial perception data at a fixed acquisition rate, forming part of the sensing pipeline synchronised via the hardwarelevel system clock as defined in the localised edge-processing module.

[0194]

[0198] The system 1000 comprises a first robotic arm 2203 and a second robotic arm 2221 , each configured as a multi-degree-of-freedom manipulator mounted on a shared horizontal translational axis 2223. The translational axis 2223 enables coordinated lateral movement of both robotic arms relative to a patient workspace, facilitating sequential and cooperative execution of scanning, fluid dispensing, and hygieneoperations in accordance with the system 1000 workflow. Each robotic arm is actuated via high-resolution servo drive assemblies 2217 and 2222, configured to provide precise joint-level control and torque regulation necessary for executing kinematically optimised trajectories generated by the edge-processing module. The first robotic arm 2203 is shown equipped with an ultrasound transducer probe end-effector 2202, configured for acoustic data acquisition from a biological target. The second robotic arm 2221 is configured to selectively mount alternative end-effectors including a gel dispenser end-effector 2218, enabling controlled application of acoustic coupling medium during pre-scan preparation.

[0195]

[0199] The system 1000 further comprises docking interfaces enclosed within docking pod visors 2204 and 2216, configured to house passive mechanical tool exchange stations located at distal extremities of the translational axis, thereby enabling automated attachment and detachment of end-effectors without active actuation mechanisms. A human-machine interface (HMI) 2205 is mounted on a vibration-isolated articulated joint 2206, enabling operator interaction while minimising transmission of mechanical vibrations to the display unit. An emergency stop button 2207 is positioned on the chassis to provide immediate system shutdown capability in response to abnormal operating conditions.

[0196]

[0200] The system 1000 is supported on a structural chassis defined by a chassis bottom 2208, mounted on castor wheels 2209 with associated locking mechanisms 2212 to stabilise the system 1000 during operation. A bottom service hatch 2210 is provided to enable maintenance access to internal subsystems including power modules and edge-processing components. A filtered air intake 2211 is configured to regulate airflow into the chassis, supporting thermal management of internal computational hardware and maintaining stable operating temperatures under continuous processing loads. The chassis further comprises a front side cover 2213, enclosing internal components, and a waste bin hatch handle 2214 providing access to an internal waste management compartment forming part of the autonomous hygiene subsystem. A push bar 2215 is provided to facilitate manual repositioning of the mobile kiosk.

[0197]

[0201] As shown, the components illustrated in Figure 4B cooperate to implement a fully integrated autonomous imaging workflow, wherein the robotic arms 2203, 2221 traverse along the horizontal axis 2223, guided by spatial perception data generated by the vision suite.

[0202] The high-resolution servo drives 2217, 2222 execute motor commands derived from inverse kinematics solutions generated by the localised edge-processing module, enabling precise probe positioning and controlled force interaction with a patient.

[0198]

[0203] The docking pod visors 2204, 2216 protect and spatially define the passive tool exchange interfaces, while the gel dispenser 2218 and ultrasound probe 2202 are selectively deployed during pre-scan and scanning phases, respectively.

[0199]

[0204] The chassis-mounted subsystems including thermal management, power infrastructure, and safety controls operate continuously to maintain system performance and ensure safe clinical operation.

[0200]

[0205] Advantageously, the configuration illustrated in Figure 4B demonstrates a mechanically compact and functionally integrated system in which robotic actuation, sensing, and control subsystems are co-located and synchronised within a single mobile platform, enabling real-time operation, reduced mechanical vibration interference, and fully autonomous execution of clinical ultrasound workflows without reliance on external infrastructure or continuous human intervention.

[0201]

[0206] Figure 4C illustrates a rear-side elevation view 1006 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the structural integration of the kinetic isolation gantry, robotic actuation subsystem, end-effector configuration, and chassis-level service and consumable interfaces.

[0202]

[0207] The system 1000 comprises a kinetic isolation gantry supported by a vertical gantry pillar 2311 , mounted to the chassis via a vibration isolation mount 2310, configured to attenuate transmission of high-frequency mechanical vibrations generated by robotic actuation.

[0203]

[0208] A primary three-dimensional spatial camera 2302 is mounted at an elevated distal position via a vibration isolation mount 2301 , such that the camera is aligned substantially above a calculated center of gravity (CoG) of the operational workspace, thereby ensuring accurate spatial perception and depth mapping.

[0204]

[0209] A surveillance PTZ camera 2312 is mounted on the gantry via an additional vibration isolation mount 2313, configured to provide continuous monitoring of the patient interaction zone and system operation.

[0205]

[0210] The vibration-isolated mounting architecture ensures that all vision sensors operate under mechanically decoupled conditions, thereby preserving spatial fidelity of captured data at a fixed acquisition rate as required by the sensing pipeline.

[0211] The system 1000 comprises a collaborative robotic manipulation assembly including a robotic arm mounted on a horizontal translational axis 2305, configured to enable lateral traversal across the patient workspace.

[0206]

[0212] The robotic arm is actuated via a high-resolution servo drive 2304, configured to execute joint-level motion commands derived from inverse kinematics solutions generated by the localised edge-processing module. The robotic arm is shown equipped with a gel and cleaning end-effector 2303, configured to perform both prescan coupling medium application and post-scan hygiene operations, thereby supporting the autonomous clinical workflow.

[0207]

[0213] A human-machine interface 2314 is mounted on the upper chassis region, configured to provide operator access to system controls, operational modes, and diagnostic information, and to interface with the localised edge-processing module for real-time system monitoring.

[0208]

[0214] The system 1000 comprises a gel refill port 2308, configured to enable replenishment of acoustic coupling medium supplied to the fluid dispensing subsystem, which in preferred embodiments maintains the coupling medium at a controlled temperature.

[0209]

[0215] A waste bin hatch 2306 is provided on the chassis, configured to interface with an internal waste management compartment associated with the autonomous hygiene subsystem, enabling removal and replacement of disposed consumables.

[0210]

[0216] The system 1000 comprises a structural chassis enclosed by a side cover 2309, providing protection to internal components including the localised edge-processing module, power infrastructure, and thermal management systems. The chassis is supported on a plurality of castor wheels 2307, enabling mobility of the system 1000 across deployment environments while maintaining stability during operation when wheel locking mechanisms are engaged.

[0211]

[0217] As shown, the vibration-isolated gantry ensures that the primary spatial camera 2302 and PTZ camera 2312 generate stable, high-fidelity visual data, which is synchronised with robotic motion commands via the Local Historian operating at a fixed 30 Hz cycle. The servo-driven robotic arm, actuated via the high-resolution servo drive 2304, executes motion trajectories derived from the dual-stage artificial intelligence pipeline comprising a perception module and reinforcement learning agent, thereby enabling precise positioning of the gel and cleaning end-effector 2303.

[0218] The gel refill port 2308 and waste bin hatch 2306 enable continuous operation of the autonomous hygiene subsystem, supporting pre-scan preparation and postscan cleaning phases. The integrated configuration ensures that sensing, actuation, and hygiene subsystems operate in a coordinated and deterministic manner within a self-contained mobile chassis.

[0212]

[0219] Advantageously, the configuration illustrated in Figure 4C provides a mechanically stable and spatially optimised arrangement of sensing and actuation components, wherein vibration-isolated vision systems are geometrically aligned with the robotic workspace, and consumable management interfaces are integrated into the chassis to support continuous autonomous operation. This configuration enhances spatial accuracy, reduces sensing noise, and enables fully autonomous clinical workflows without reliance on external infrastructure or manual intervention.

[0213]

[0220] Figure 4D illustrates a side elevation view 1008 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the integration of the robotic actuation subsystem, vision sensing components, operator interface elements, and chassis-mounted control and service interfaces.

[0214]

[0221] The system 1000 comprises a multi-modal vision suite including an auxiliary three-dimensional spatial camera 2412, mounted on a vibration isolation mount configured to attenuate mechanical disturbances generated by robotic motion.

[0215]

[0222] A PTZ surveillance camera 2401 is positioned on the gantry structure to provide continuous visual monitoring of the patient interaction zone and system operation.

[0216]

[0223] The vision components are mechanically coupled to the gantry via vibration isolation mount 2403, thereby ensuring that spatial perception data remains stable and free from motion-induced noise.

[0217]

[0224] The system 1000 comprises a robotic manipulation assembly actuated via a high-resolution AC servo drive 2410, configured to provide joint-level control of the robotic arm.

[0218]

[0225] The robotic arm is shown equipped with an ultrasound probe end-effector 2411 , configured for acoustic data acquisition and adapted to interface with a hybrid activepassive compliant mechanism for controlled contact force application.

[0219]

[0226] The servo drive 2410 executes motion commands derived from inverse kinematics outputs generated by the localised edge-processing module, thereby enabling precise probe positioning relative to a biological target.

[0227] A human-machine interface (HMI) 2402 is mounted to the chassis via a mounting clamp 2404, configured to provide a stable yet adjustable interface for operator interaction. The HMI 2402 enables access to system modes including autonomous operation and telerobotic learning modes, and displays real-time system telemetry, imaging data, and safety status.

[0220]

[0228] The system 1000 comprises an emergency stop button 2408, configured to immediately terminate all robotic motion upon activation.

[0221]

[0229] A power control interface 2409 is provided, comprising a multi-colour illumination system configured to visually indicate system operational states, including a red state indicating STOP condition, an orange state indicating STANDBY condition, and a green state indicating RUN condition. The visual state signalling provides immediate operator feedback and ensures compliance with clinical safety protocols and human-machine interaction standards.

[0222]

[0230] The system 1000 comprises a probe cleaner solution refill port 2407, configured to supply cleaning agents to the autonomous hygiene subsystem, including probe sanitisation processes executed post-scan. The refill port 2407 is fluidically connected to internal cleaning reservoirs and delivery systems, supporting automated hygiene cycles as defined in the operational workflow.

[0223]

[0231] The system 1000 comprises a structural chassis enclosed by a side cover 2405, providing protection to internal components including the localised edge-processing module, power infrastructure, and thermal management systems. The chassis is supported on castor wheels 2406, enabling mobility of the system 1000 across deployment environments while maintaining positional stability during operation when locking mechanisms are engaged.

[0224]

[0232] As shown, the auxiliary spatial camera 2412 and PTZ camera 2401 generate real-time spatial and monitoring data, which is synchronised via a hardware-level system clock operating at 30 Hz within the Local Historian, forming part of the sensing pipeline. The high-resolution servo drive 2410 executes motion trajectories generated by the dual-stage artificial intelligence pipeline, wherein a perception module calculates spatial error metrics and a reinforcement learning agent optimises probe positioning. The ultrasound probe end-effector 2411 interacts with the patient under strict mechanical admittance control, while the HMI 2402 provides real-time system visibility and operator override capability.

[0233] The safety interfaces including the emergency stop 2408 and state-indicating power control 2409 ensure that system operation remains within predefined safety thresholds, while the refill port 2407 enables continuous operation of the hygiene subsystem. The integrated configuration ensures coordinated operation of sensing, actuation, control, and hygiene subsystems within a self-contained mobile platform.

[0225]

[0234] Advantageously, the configuration illustrated in Figure 4D provides a tightly integrated control and actuation interface in which robotic motion, spatial sensing, operator interaction, and safety mechanisms are co-located and synchronised within a single structural platform. This arrangement enables real-time probe control, enhanced operator situational awareness, and compliant clinical operation while maintaining full system autonomy and deployment independence.

[0226]

[0235] Figure 4E illustrates a top plan view 1010 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the spatial integration of the collaborative dual-robotic manipulation assembly, multi-modal vision suite, endeffector docking ecosystem, and autonomous hygiene and consumable management subsystem.

[0227]

[0236] The system 1000 comprises a first robotic arm 2509 mounted on a shared horizontal translational axis 2520, configured to enable lateral traversal across a patient workspace. The robotic arm 2509 is actuated via high-resolution AC servo drives 2510 and 2511 , configured to execute joint-level motion commands derived from inverse kinematics solutions generated by the localised edge-processing module.

[0228]

[0237] A J6 face plate 2503 is positioned at the terminal joint of the robotic arm, supporting a 6-axis force-torque sensor 2504 mounted exclusively at the final joint, thereby enabling strict mechanical admittance control during probe-patient interaction.

[0229]

[0238] An ultrasound transducer probe end-effector 2508, carrying an ultrasound probe 2506, is operatively coupled to the robotic arm, configured to acquire ultrasonic data while maintaining controlled contact force as regulated by the force-torque sensor 2504.

[0230]

[0239] The system 1000 further comprises an autonomous fluid dispensing subsystem including an end-effector gel refill port 2512 and a gel dispensing nozzle 2513, configured to deliver acoustic coupling medium to a biological target. The dispensing subsystem is configured to operate in conjunction with the robotic manipulation assembly, wherein a fluid dispensing end-effector is selectively attached via docking interfaces and deployed during pre-scan preparation. A cleaning towel bin 2519 isintegrated within the chassis, configured to supply high-absorption sanitisation materials to a cleaner end-effector during post-scan hygiene operations. A waste bin chute cover 2514 is provided to facilitate controlled disposal of used materials into an internal waste management compartment forming part of the autonomous hygiene ecosystem.

[0231]

[0240] The system 1000 comprises a plurality of docking stations located at distal extremities of the translational axis 2520, including a probe end-effector docking station 2524, a gel dispenser docking pod 2516, a cleaner end-effector docking pod 2515, and an auxiliary docking pod 2518. Each docking station is configured to interface with a passive mechanical tool changer comprising precision alignment features and inverse-profile latching mechanisms, enabling automated attachment and detachment of end-effectors without active pneumatic or electromagnetic actuation.

[0232]

[0241] The system 1000 comprises a multi-modal vision suite including a primary three-dimensional spatial camera 2507 and an auxiliary three-dimensional spatial camera 2505, configured to generate volumetric depth maps of the patient workspace. A surveillance PTZ camera 2521 is mounted on a vibration-isolated gantry via a vibration isolation mount 2522, configured to provide continuous monitoring and supervisory observation. The cameras are arranged such that the primary spatial camera 2507 is aligned substantially above a calculated center of gravity of the operational workspace, while the auxiliary spatial camera 2505 is positioned to mitigate occlusion, thereby ensuring robust spatial perception. A human-machine interface 2501 is mounted via a collar 2502 and further supported by a vibration isolation mount 2523, configured to provide operator access to system controls while minimising transmission of mechanical vibrations from the chassis. The HMI 2501 interfaces with the localised edge-processing module to display real-time system status, imaging data, and operational parameters.

[0233]

[0242] The system 1000 comprises a structural chassis incorporating a push bar 2517, enabling manual repositioning of the mobile kiosk across deployment environments.

[0234]

[0243] As shown in Figure 4E, the robotic arm 2509 traverses along the horizontal axis 2520, executing motion trajectories derived from the dual-stage artificial intelligence pipeline comprising a perception module and reinforcement learning agent.

[0235]

[0244] The force-torque sensor 2504 continuously regulates contact forces applied by the ultrasound probe 2506, ensuring stable acoustic coupling while preventingexcessive force. The vision suite comprising cameras 2505, 2507, 2521 generates spatial perception data synchronised at 30 frames-per-second and time-aligned with robotic command signals via a hardware-level system clock operating at 30 Hz, forming a closed-loop control system. The docking stations 2515, 2516, 2518, 2524 enable automated switching between scanning, fluid dispensing, and cleaning endeffectors, supporting a fully autonomous clinical workflow including pre-scan preparation, scanning execution, and post-scan hygiene. The towel bin 2519 and waste chute 2514 cooperate with the cleaner end-effector to enable automated waste handling, thereby eliminating manual intervention during hygiene cycles.

[0236]

[0245] Advantageously, the configuration illustrated in Figure 4E provides a tightly integrated robotic, sensing, and hygiene ecosystem in which perception, actuation, and consumable management subsystems are co-located and synchronised within a single platform. This enables closed-loop ultrasound imaging with automated tool exchange and hygiene management, thereby enhancing imaging precision, operational efficiency, and deployment independence in clinical and remote environments.

[0237]

[0246] Figure 4F illustrates a bottom plan view 1012 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the micro-level integration of end-effector coupling interfaces, fluid dispensing components, proximity sensing elements, and structural chassis features.

[0238]

[0247] The system 1000 comprises a structural trolley chassis bottom 2602, configured to provide a rigid load-bearing platform supporting the robotic manipulation assembly, end-effector docking infrastructure, and internal subsystems.

[0239]

[0248] A human-machine interface mounting clamp bolt 2601 is provided to secure the HMI assembly to the chassis, ensuring stable operator interface positioning under dynamic system operation.

[0240]

[0249] The system 1000 comprises a cleaner end-effector coupling interface 2603, configured as a J6 terminal joint attachment mechanism enabling mechanical and functional coupling of a cleaner end-effector to a robotic arm. A 6-axis force-torque sensor 2608 is integrated within the cleaner end-effector assembly, configured to measure multi-axis force and torque vectors during interaction with a biological surface, thereby enabling strict mechanical admittance control. The force-torque sensor 2608 operates in conjunction with the localised edge-processing module, whichprocesses sensor feedback in real time to regulate applied forces and maintain safe contact conditions.

[0241]

[0250] The system 1000 comprises a gel dispensing nozzle 2605, configured to deliver an acoustic coupling medium onto a target surface. A gel dispenser refill port 2606 is fluidically connected to an internal reservoir and micro-pumping system, enabling replenishment of the coupling medium and supporting continuous operation of the fluid dispensing subsystem. The dispensing system is configured to operate under controlled flow conditions, and in preferred embodiments includes thermal regulation to maintain the fluid at a predefined temperature suitable for clinical application. The system 1000 comprises a Time-of-Flight (ToF) infrared sensor 2604, positioned adjacent to the gel dispensing nozzle 2605, configured to detect the distance between the end-effector and a target surface. The ToF sensor 2604 enables a perpendicular micro-approach control mechanism, allowing the robotic system to precisely regulate approach distance during fluid dispensing and cleaning operations, thereby preventing premature contact or excessive force application. Sensor data from the ToF sensor 2604 is integrated into the closed-loop control system, enabling real-time adjustment of robotic motion trajectories during end-effector deployment.

[0242]

[0251] A primary three-dimensional spatial camera 2607 is positioned relative to the end-effector workspace, configured to provide spatial reference data for coordinating robotic motion and end-effector positioning. The spatial camera 2607 operates in conjunction with the ToF sensor 2604 and force-torque sensor 2608, forming a multilayered sensing architecture combining visual, proximity, and force feedback.

[0243]

[0252] The system 1000 further comprises an ultrasound transducer probe 2609, configured to be mounted to a probe end-effector assembly and used for acoustic data acquisition. The probe 2609 is operatively coupled to the robotic manipulation assembly via a compliant end-effector structure, enabling controlled contact with a patient while maintaining consistent acoustic coupling conditions.

[0244]

[0253] As shown in Figure 4F, the ToF sensor 2604, force-torque sensor 2608, and spatial camera 2607 operate in a coordinated manner to provide multi-modal feedback to the localised edge-processing module.

[0245]

[0254] The edge-processing module executes a dual-stage artificial intelligence pipeline, wherein perception algorithms determine spatial positioning and a reinforcement learning agent optimises motion trajectories, with outputs translated into joint-level commands via an inverse kinematics solver.

[0255] The fluid dispensing subsystem, comprising the nozzle 2605 and refill port 2606, operates in synchronisation with robotic motion to deliver controlled volumes of acoustic gel to a target surface prior to ultrasound scanning.

[0246]

[0256] The cleaner end-effector coupling 2603, in conjunction with the force-torque sensor 2608, enables controlled cleaning operations during post-scan hygiene cycles, including wiping and waste disposal as part of the autonomous hygiene ecosystem.

[0247]

[0257] Advantageously, the configuration illustrated in Figure 4F provides a fully integrated micro-level sensing and actuation architecture in which proximity sensing, force feedback, and fluid dispensing are co-located within the end-effector assembly. This enables highly precise, closed-loop control of end-effector interaction with a biological surface, thereby improving safety, reducing operational error, and enabling fully autonomous execution of clinical ultrasound workflows.

[0248]

[0258] Figure 4G illustrates a rear elevational view 1014 of the fully autonomous clinical robotic ultrasound imaging system 1000 of Figure 3, showing the integration of robotic manipulation assemblies, edge-processing infrastructure, thermal management systems, operator interface components, and network communication interfaces.

[0249]

[0259] The system 1000 comprises a first robotic manipulation unit in the form of a 7-degree-of-freedom robotic arm 2723, and a second robotic manipulation unit in the form of a 7-degree-of-freedom robotic arm 2704, configured to operate collaboratively on a shared workspace. Each robotic arm is driven by a plurality of high-resolution AC servo drives 2702, 2703, 2705, 2706, 2707, configured to provide precise joint-level actuation and enable smooth trajectory execution under control of the localised edgeprocessing module. The robotic arms are configured to traverse a shared horizontal translational axis enabling coordinated scanning operations across a patient workspace. A robotic arm back panel 2724 encloses internal actuator wiring, drive electronics, and signal routing pathways, thereby protecting sensitive components while maintaining service accessibility.

[0250]

[0260] The system 1000 further comprises a multi-modal vision suite including a primary three-dimensional spatial camera 2701 , an auxiliary three-dimensional spatial camera 2721 , and a surveillance pan-tilt-zoom (PTZ) camera 2722. The cameras are mounted on a vibration-isolated gantry structure, ensuring that high-frequency vibrations generated by robotic actuation do not degrade visual perception accuracy.

[0261] The primary spatial camera 2701 is configured to capture volumetric depth data aligned with the system’s operational space digital twin, while the auxiliary spatial camera 2721 provides occlusion mitigation. The PTZ camera 2722 provides supervisory imaging and situational awareness for system monitoring and remote observation.

[0251]

[0262] The system 1000 comprises a controller and edge-processing unit assembly housed within an enclosed compartment accessible via a dedicated hatch 2715.

[0252]

[0263] The edge-processing module operates as a localised computational core configured to execute perception, trajectory planning, inverse kinematics, and predictive maintenance algorithms.

[0253]

[0264] The enclosure is designed to provide electromagnetic shielding and thermal isolation for high-performance compute hardware.

[0254]

[0265] A high-speed cooling fan 2708 is integrated within the rear panel to provide active airflow for thermal regulation of the edge-processing module and associated electronics.

[0255]

[0266] The cooling system is configured to maintain stable operating temperatures under continuous computational load, ensuring performance of real-time Al and control systems.

[0256]

[0267] The system 1000 comprises network and data ports 2711, configured to support high-speed communication via Gigabit Ethernet, USB 3.1 , and CAN Bus interfaces.

[0257]

[0268] These ports enable interconnection between internal subsystems and external devices, and facilitate execution of a store-and-forward synchronisation protocol for transmitting operational data to a remote monitoring server upon restoration of network connectivity.

[0258]

[0269] The system 1000 further comprises an accessory and tools drawer 2710, configured to store service tools, replacement components, and consumables required for system maintenance.

[0259]

[0270] A bottom service hatch 2713 provides access to internal subsystems including power electronics, battery modules, and structural mounting interfaces.

[0260]

[0271] A US probe station side back panel 2716 provides localised access to probe docking and associated subsystem interfaces.

[0261]

[0272] A back side panel 2709 encloses the rear structure, providing protection while allowing modular access for servicing.

[0273] The system 1000 comprises an emergency stop button 2717, configured to immediately arrest all robotic motion and disable system operation in response to a safety event. A human-machine interface (HMI) 2720 is mounted via a vibration isolation mount 2719 and vibration isolation joint 2718, thereby ensuring stable operator interaction independent of chassis or robotic vibration. The system 1000 is supported by a plurality of castor wheels 2714, enabling mobility of the van-transportable kiosk. Each castor wheel includes a locking mechanism 2712, configured to secure the system 1000 in a fixed position during operation, thereby maintaining stability and ensuring accurate spatial calibration.

[0262]

[0274] As shown, the components illustrated in Figure 4G collectively provide a fully integrated rear-side infrastructure supporting high-performance localised edge computation, real-time robotic actuation via servo-controlled joints, multi-modal visionbased spatial perception, secure data communication and storage, active thermal management, safe human-machine interaction.

[0263]

[0275] The integration of network interfaces, cooling systems, and processing units enables the system 1000 to operate independently of continuous cloud connectivity, while maintaining full functionality for autonomous imaging, data acquisition, and predictive maintenance.

[0264]

[0276] Advantageously, the configuration illustrated in Figure 4G provides a fully enclosed, thermally managed, and network-integrated control architecture that enables reliable deployment of a fully autonomous clinical imaging system in noncontrolled environments. The integration of edge-processing, real-time control hardware, and secure communication interfaces within a mobile chassis ensures system performance, reduced latency, and compliance with medical-grade operational and cybersecurity requirements.

[0265]

[0277] Figure 5 illustrates a hybrid active-passive compliant end-effector assembly 300 configured to serve as a probe shock absorber and force-regulated interface between a robotic manipulation assembly and a biological target.

[0266]

[0278] The assembly 300 comprises a protective shroud 301 , configured to enclose internal sensing components and shield them from environmental contamination and mechanical damage during operation. A plurality of Time-of-Flight (ToF) infrared sensor ports 302 are provided within the shroud 301 , configured to house proximity sensing elements that detect the distance between the end-effector and a biological surface. The ToF sensor ports 302 are positioned to enable perpendicular micro-approach sensing, thereby facilitating precise pre-contact positioning and controlled approach trajectories. The assembly 300 comprises an end-effector joint coupling plate 303, configured to mechanically interface with a terminal robotic joint (J6) of the robotic manipulation assembly. A plurality of bolt holes 304 are provided in the coupling plate 303, enabling secure attachment to the robotic arm and ensuring structural rigidity under dynamic loading conditions.

[0267]

[0279] A cable exit 305 is provided to route electrical wiring associated with sensors and the ultrasound probe, enabling communication with the localised edge-processing module.

[0268]

[0280] The compliant assembly 306 comprises a rigid upper housing coupled to a floating lower carriage via a plurality of compression springs 310, configured to provide passive compliance along a primary axis of motion.

[0269]

[0281] The springs 310 are arranged symmetrically and are pre-compressed to establish a predefined breakaway force threshold, mathematically defined as:

[0270]

[0271]

[0282] Each compression spring 310 is geometrically constrained such that its free length divided by its mean diameter satisfies a slenderness ratio of:

[0272]

[0273] thereby rendering the springs inherently resistant to lateral buckling independent of internal guide structures.

[0274]

[0283] The floating carriage is constrained to linear motion via a pair of rigid guide structures comprising roller bearings and pins 309, which are inserted into corresponding vertical guide cavities defined by vertical holes 312.

[0275]

[0284] The roller bearing and pin assemblies 309 ensure that the carriage translates along a controlled axis, thereby preventing rotational or lateral displacement during compression.

[0276]

[0285] A cable hole 311 is provided within the assembly to route internal wiring through the moving carriage without mechanical interference.

[0277]

[0286] The assembly 300 further comprises a probe holder 307, configured to securely retain an ultrasonic transducer probe 308.

[0287] The probe 308 is positioned such that it maintains consistent contact with a biological surface during operation, with the compliant mechanism absorbing dynamic forces and maintaining stable acoustic coupling. A 6-axis force-torque sensor 313 is mounted proximally to the coupling plate 303, configured to measure multi-axis force and torque vectors generated during probe contact. The force-torque sensor 313 operates in conjunction with the compliant mechanism 306, providing real-time feedback to the localised edge-processing module to regulate applied forces and maintain safe interaction with the patient.

[0278]

[0288] As shown in Figure 5, the ToF sensors located within ports 302 detect the proximity of a biological surface, enabling controlled approach of the end-effector prior to contact. Upon contact, the compliant mechanism 306 allows controlled compression of the springs 310, thereby absorbing impact forces and maintaining a consistent contact pressure. The roller-guided carriage defined by components 309 and 312 ensures linear displacement, preserving probe alignment and preventing off-axis loading. The force-torque sensor 313 continuously monitors applied forces, enabling the control system to adjust robotic motion via inverse kinematics and reinforcement learning-based trajectory optimisation. Advantageously, the hybrid active-passive compliant end-effector assembly 300 illustrated in Figure 5 provides a mechanically robust and mathematically predictable force-regulation interface that combines passive compliance with active sensing. This configuration enables precise control of probe contact forces, reduces the risk of patient discomfort or injury, and ensures consistent acoustic coupling, thereby enhancing imaging accuracy and system reliability.

[0279]

[0289] Figure 6 illustrates a passive dynamic end-effector exchange coupling 400 configured to enable automatic tool attachment and detachment at distal extremities of the robotic system without the use of active pneumatic, hydraulic, or electromagnetic actuation. The coupling comprises an ATC master plate 401, configured to be rigidly mounted to a terminal joint of a robotic arm. A plurality of bolt holes 402 are provided to facilitate secure mechanical fastening of the master plate 401 to the robotic structure, ensuring transmission of torque and axial loads during operation. A latch lock cavity 403 is formed within the master plate 401 , configured to receive and mechanically engage a corresponding latch element of a mating slave plate. A hole for cable pass-through 404 is provided to enable routing of electrical wiring and signal lines through the coupling interface while maintaining mechanicalisolation. The master plate further comprises a latch coupler barrel 405, configured to house internal latch engagement geometry and guide mechanical coupling during docking. A plurality of precision alignment pins 406 extend from the master plate 401 , configured to engage corresponding alignment pin holes on the slave plate to ensure accurate positional registration. An electrical connector port 407 is integrated within the master plate 401 , configured to establish electrical continuity with a corresponding connector on the slave plate upon coupling. The coupling 400 further comprises an ATC slave plate 408, configured to be rigidly integrated with an interchangeable endeffector, including but not limited to an ultrasound probe, gel dispenser, or cleaning tool. A hole for cable pass-through 409 is provided in the slave plate 408 to route internal wiring from the end-effector to the connector interface. A plurality of pogo pins 410 are arranged on the slave plate 408, configured to establish spring-loaded electrical contact with the electrical connector port 407 of the master plate during coupling. The slave plate 408 further comprises one or more latch elements 411 , configured to mechanically engage with the latch lock cavity 403 of the master plate. A plurality of bolt holes 412 are provided to secure the slave plate 408 to the endeffector structure. The latch elements 411 are configured to engage the latch lock cavity 403 through purely mechanical interaction, thereby securing the slave plate 408 to the master plate 401 without requiring active actuation. A plurality of latch release buttons 413 are positioned on the slave plate 408, configured to mechanically disengage the latch elements 411 when simultaneously actuated. The latch mechanism is configured such that engagement occurs automatically upon insertion and alignment of the plates, while disengagement requires coordinated mechanical actuation, thereby preventing accidental decoupling. A plurality of alignment pin holes 414 are provided on the slave plate 408, configured to receive the alignment pins 406 of the master plate. The engagement between alignment pins 406 and alignment pin holes 414 ensures precise radial and axial alignment of the coupling interface. The pin-hole interface further provides anti-rotation constraint, preventing torsional misalignment and ensuring consistent orientation of the end-effector during operation.

[0280]

[0290] Upon coupling, the pogo pins 410 engage the electrical connector port 407, thereby establishing electrical communication between the robotic arm and the attached end-effector. The spring-loaded nature of the pogo pins 410 compensates for minor mechanical tolerances and ensures reliable electrical contact under dynamic loading conditions.

[0291] As shown in Figure 6, the robotic arm positions the master plate 401 in alignment with the slave plate 408 located at a docking station positioned at the distal extremity of a horizontal translational axis. As the plates are brought into contact, the alignment pins 406 enter the alignment pin holes 414, guiding the coupling interface into precise alignment. Continued insertion causes the latch elements 411 to engage the latch lock cavity 403, thereby mechanically securing the slave plate 408 to the master plate 401. Simultaneously, the pogo pins 410 establish electrical contact with the connector port 407, enabling data and power transmission. Detachment is achieved by actuating the latch release buttons 413, thereby disengaging the latch elements 411 and allowing separation of the plates. The coupling mechanism operates entirely via passive mechanical interaction, with no reliance on active pneumatic, electromagnetic, or motorised actuation. Engagement and disengagement are achieved through controlled robotic positioning and mechanical interaction, including a predefined rotational or translational motion executed by the robotic arm. This passive configuration enhances system reliability, reduces maintenance complexity, and eliminates failure modes associated with active coupling systems.

[0281]

[0292] Advantageously, the passive dynamic end-effector exchange coupling 400 illustrated in Figure 6 provides a mechanically robust, self-aligning, and electrically integrated interface that enables rapid and reliable tool exchange without active actuation. The use of precision alignment pins, inverse-profile latch engagement, and spring-loaded electrical contacts ensures repeatable coupling accuracy, minimizes mechanical wear, and supports continuous autonomous operation in clinical environments.

[0282]

[0293] Figure 7 illustrates an automated hygiene and consumable replenishment subsystem 500 configured to support autonomous pre-scan preparation, post-scan cleaning, and continuous consumable management within the portable imaging system 100 of Figure 1, in accordance with an embodiment of the present invention. The subsystem 500 comprises a sanitisation tub and body 504, configured to receive an ultrasound transducer probe end-effector 501 following completion of a scanning procedure. The sanitisation tub 504 is fluidically connected to a plumbing pipe 505, which supplies cleaning agents from an internal reservoir. A cleaning solution refill inlet 506 is provided to enable replenishment of sanitisation fluids into the system. A cleaning solution smart storage tank 508 is integrated into the base structure 507, configured to store and regulate the supply of cleaning solution delivered to thesanitisation tub 504. The subsystem 500 is configured to automatically initiate probe cleaning upon docking of the probe end-effector 501 , including controlled fluid dispensing and containment within the tub. The subsystem 500 further comprises a plurality of smart docking station ports 502 housed within a smart docking station body 503, configured to interface with multiple end-effectors including ultrasound probes, gel dispensers, and cleaning tools. The docking station ports 502 provide both mechanical retention and electrical connectivity, enabling charging, data communication, and readiness verification of docked end-effectors. A gel dispenser and cleaner end-effector smart dock 512 is provided, configured to store and manage fluid dispensing and cleaning end-effectors when not in active use. The subsystem 500 comprises a smart cleaning towel bin 516, configured to store disposable cleaning towels 515. The towels 515 are mounted on a disposable towel dowel 513, which is electrically interfaced via a base metal contact 514, enabling detection of towel presence and inventory status. The towel bin 516 further comprises an auto-opening cover 517, configured to open in response to a command from the control system during cleaning operations. The subsystem 500 is configured such that a cleaner endeffector, comprising an electromagnetic pickup mechanism, retrieves a towel 515 from the bin 516 for use in post-scan patient cleaning. The subsystem 500 further comprises a smart waste bin 509, configured to receive and contain used consumables including cleaning towels. A waste disposal window 511 and a waste bin chute 519 are provided to guide disposed materials into the bin 509. The waste bin 509 further comprises an auto-cover 518, configured to automatically open during waste disposal and close thereafter to maintain hygiene and containment. A waste bag removal hatch 510 is provided to enable manual removal and replacement of waste bags within the bin. The subsystem 500 is mounted on a base plate 507, which provides structural support and integrates fluid storage, waste management, and docking components into a unified assembly. A plurality of removable assembly panels 520 are provided to allow access to internal components including fluid reservoirs, plumbing connections, and electrical interfaces for maintenance and servicing.

[0283]

[0294] As shown in Figure 7, during pre-scan preparation, a robotic arm retrieves a gel dispenser end-effector from the docking station 512 and applies acoustic gel to a target surface. During post-scan hygiene, a robotic arm retrieves a cleaner endeffector, actuates the towel bin cover 517, and acquires a disposable towel 515 via electromagnetic pickup. The robotic arm then performs cleaning of the biologicalsurface and deposits the used towel into the waste bin 509 via the chute 519, triggering the auto-cover 518. The ultrasound probe end-effector 501 is subsequently docked into the sanitisation tub 504, where automated cleaning is performed using fluid supplied from the storage tank 508 via plumbing 505. The subsystem 500 operates in coordination with the localised edge-processing module and robotic manipulation assembly, forming an integrated hygiene loop. Advantageously, the automated hygiene and consumable replenishment subsystem 500 illustrated in Figure 7 provides a fully integrated, closed-loop hygiene architecture that enables autonomous management of cleaning, waste disposal, and consumable replenishment without human intervention. This configuration ensures consistent clinical hygiene standards, reduces operator workload, and enables deployment of the system 100 in remote or resource-limited environments where trained personnel may not be available.

[0284] Interpretation

[0285] Markush Groups

[0286]

[0295] In addition, where features or aspects of the invention are described in terms of Markush groups, those skilled in the art will recognise that the invention is also thereby described in terms of any individual member or subgroup of members of the Markush group.

[0287] Chronological sequence

[0288]

[0296] For this specification, where method steps are described in sequence, the sequence does not necessarily mean that the steps are to be carried out in chronological order in that sequence, unless there is no other logical manner of interpreting the sequence.

[0289] Embodiments:

[0290]

[0297] Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment but may. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner, as would be apparent to one of ordinary skill in the art from this disclosure, in one or more embodiments.

[0298] Similarly, it should be appreciated that in the above description of example embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the Description of Embodiments are hereby expressly incorporated into this Description of Embodiments, with each claim standing on its own as a separate embodiment of this invention.

[0291]

[0299] Furthermore, while some embodiments described herein include some, but not other features included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention, and form different embodiments, as would be understood by those in the art. For example, in the following claims, any of the claimed embodiments can be used in any combination. Different Instances of Objects

[0292]

[0300] As used herein, unless otherwise specified the use of the ordinal adjectives “first”, “second”, “third”, etc., to describe a common object, merely indicate that different instances of like objects are being referred to and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

[0293] Specific Details

[0294]

[0301] In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In other instances, well-known methods, structures, and techniques have not been shown in detail in order not to obscure an understanding of this description.

[0295] Terminology

[0296]

[0302] In describing the preferred embodiment of the invention illustrated in the drawings, specific terminology will be resorted to for the sake of clarity. The invention is, however, not intended to be limited to the specific terms so selected, and it is to be understood that each specific term includes all technical equivalents which operate in a similar manner to accomplish a similar technical purpose. Terms such as "forward","rearward", "radially", "peripherally", "upwardly", "downwardly", and the like are used as words of convenience to provide reference points and are not to be construed as limiting terms.

[0297]

[0303] As used herein the term “and / or” means “and” or “or” or both.

[0298]

[0304] As used herein “(s)” following a noun means the plural and / or singular forms of the noun.

[0299] Comprising and Including

[0300]

[0305] In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word “comprise” or variations such as “comprises” or “comprising” are used in an inclusive sense, i.e., to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention.

[0301]

[0306] Any one of the terms: including or which includes or that includes as used herein is also an open term that also means including at least the elements / features that follow the term but not excluding others. Thus, including is synonymous with and means comprising.

[0302]

[0307] The features disclosed may, separately, or in any combination of such features, be utilised for realising the invention in diverse forms thereof.

[0303] Scope of Invention

[0304]

[0308] Thus, while there has been described what are believed to be the preferred embodiments of the invention, those skilled in the art will recognize that other and further modifications may be made thereto without departing from the spirit of the invention, and it is intended to claim all such changes and modifications as fall within the scope of the invention. For example, any formulas given above are merely representative of procedures that may be used. Functionality may be added or deleted from the block diagrams and operations may be interchanged among functional blocks. Steps may be added or deleted to methods described within the scope of the present invention.

[0305]

[0309] It will be appreciated that specific algorithmic implementations, machine learning architectures, training parameters, and mathematical models described herein are provided by way of example only and are not intended to limit the scope of the invention. Alternative computational models, optimisation techniques, or dataprocessing frameworks may be employed without departing from the scope of the present invention.

[0306]

[0310] Although the invention has been described with reference to specific examples, it will be appreciated by those skilled in the art that the invention may be embodied in many other forms.

[0307] Industrial Applicability

[0308]

[0311] It is apparent from the above, that the arrangements described are applicable to the medical Al data industry, expert outsourcing industry. .

Claims

1. Claims1. A portable imaging system for performing automated ultrasound examination of one or more body parts of a user, the system comprising:a scanning assembly configured to position one or more ultrasound probes relative to the one or more body parts;one or more ultrasound probes configured to acquire ultrasound image data of the one or more body parts;a control module operatively coupled to the scanning assembly and the one or more ultrasound probes; andan image processing module configured to process the acquired ultrasound image data,wherein the control module is configured to control movement of the one or more ultrasound probes based on predetermined information relating to the one or more body parts,wherein the control module is further configured to adjust a position and / or orientation of the one or more ultrasound probes during scanning based on feedback derived from the image processing module.

2. The portable imaging system as claimed in claim 1 , wherein the scanning assembly comprises one or more robotic arms configured to be coupled with the one or more ultrasound probes.

3. The portable imaging system as claimed in claim 2, wherein the one or more robotic arms have six or more degrees of freedom.

4. The portable imaging system as claimed in claim 2 or 3, wherein the one or more robotic arms further comprise a linear axis providing translational movement.

5. The portable imaging system as claimed in any one of the preceding claims, wherein the scanning assembly further comprising one or more sensors configured to provide real-time feedback relating to force and / or contact between the one or more ultrasound probes and the one or more body parts.

6. The portable imaging system as claimed in claim 5, wherein the one or more sensors comprise a multi-axis force torque sensor.

7. The portable imaging system as claimed in any one of the preceding claims, wherein the scanning assembly comprises an end-effector assembly including a compliant mechanism.

8. The portable imaging system as claimed in any one of the preceding claims, wherein the scanning assembly comprises a vibration-isolated support structure.

9. The portable imaging system as claimed in any one of the preceding claims, wherein the vibration-isolated support structure is configured to reduce transmission of mechanical vibrations from the scanning assembly to the one or more ultrasound probes.

10. The portable imaging system as claimed in any one of the preceding claims, wherein the scanning assembly comprises a primary three-dimensional imaging device and an auxiliary three-dimensional imaging device arranged to reduce visual occlusion.

11. The portable imaging system as claimed in any one of the preceding claims, further comprising a sensing module configured to obtain spatial information of the one or more body parts.

12. The portable imaging system as claimed in any one of the preceding claims, wherein the sensing module comprises a three-dimensional imaging device configured to generate depth data or a three-dimensional model of the one or more body parts.

13. The portable imaging system as claimed in any one of the preceding claims, wherein the sensing module is configured to determine an initial position and / or orientation of the ultrasound probes based on the spatial information.

14. The portable imaging system as claimed in any one of the preceding claims, wherein the sensing module comprises proximity sensors configured to detect objects within a predefined distance.

15. The portable imaging system as claimed in any one of the preceding claims, wherein the sensing module comprises one or more inertial measurement units configured to provide calibration data.

16. The portable imaging system as claimed in any one of the preceding claims, wherein the sensing module comprises a plurality of inertial measurement units distributed across the scanning assembly, one or more robotic arms, and one or more ultrasound probes, configured to generate calibration data for compensating structural misalignment of the system.

17. The portable imaging system as claimed in claim 1 , wherein each of the one or more ultrasound probes comprises an array of transducers configured to generate and receive ultrasonic signals.

18. The portable imaging system as claimed in claim 1 , wherein the image processing module is configured to identify one or more anatomical features in the acquired ultrasound image data.

19. The portable imaging system as claimed in any one of the preceding claims, wherein the image processing module is configured to determine whether image quality satisfies one or more predefined criteria.

20. The portable imaging system as claimed in any one of the preceding claims, wherein the image processing module comprises a feature detection model and a control optimisation module.

21. The portable imaging system as claimed in any one of the preceding claims, wherein the control optimisation module comprises a machine learning model.

22. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to modify the position and / or orientation of the one or more ultrasound probes when the image quality does not satisfy the one or more predefined criteria.

23. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to modify operation of the scanning assembly based on user compliance with the instructions.

24. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to adjust the position and / or orientation of the one or more ultrasound probes based on the identified one or more anatomical features.

25. The portable imaging system as claimed in any one of the preceding claims, further comprising an analysis module configured to identify one or more areas of interest in the one or more body parts based on the processed ultrasound image data.

26. The portable imaging system as claimed in claim 20, wherein the analysis module comprises a machine learning model trained to identify one or more areas of interest.

27. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to update the position and / ororientation of the ultrasound probes using predetermined information and feedback derived from the processed ultrasound image data.

28. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to operate the system in an autonomous scanning mode.

29. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to adjust operation of the scanning assembly based on the calibration data to compensate for tilt or uneven deployment surfaces.

30. The portable imaging system as claimed in any one of the preceding claims, further comprising an interface module including a display configured to present imaging data and receive input from the user.

31. The portable imaging system as claimed in any one of the preceding claims, further comprising a communication module configured to transmit imaging results and / or identified one or more areas of interest to one or more external devices.

32. The portable imaging system as claimed in any one of the preceding claims, further comprising a support surface configured to support at least a portion of the one or more body parts during scanning.

33. The portable imaging system as claimed in any one of the preceding claims, wherein the scanning assembly comprises two or more robotic arms configured to position and manipulate the two or more ultrasound probes.

34. The portable imaging system as claimed in any one of the preceding claims, wherein the two or more robotic arms are configured to move relative to each other to cooperatively control the position and / or orientation of the two or more ultrasound probes.

35. The portable imaging system as claimed any one of the preceding claims, wherein at least one robotic arm is configured to stabilise the one or more body parts while another robotic arm positions the one or more ultrasound probes.

36. The portable imaging system as claimed in any one of the preceding claims, wherein the control module is configured to coordinate movement of the two or more robotic arms based on predetermined information and feedback derived from the processed ultrasound image data.

37. The portable imaging system as claimed in any one of the preceding claims, further comprising a data management module configured to store imaging data.

38. The portable imaging system as claimed in any one of the preceding claims, wherein the data management module comprises CAN, USB, and Ethernet interfaces.

39. The portable imaging system as claimed in any one of the preceding claims, wherein the data management module is configured to execute a store-and-forward protocol.

40. The portable imaging system as claimed in any one of the preceding claims, wherein the data management module comprises a time-synchronisation module.

41. The portable imaging system as claimed in any one of the preceding claims, wherein the data management module is configured to encrypt and securely transmit data.

42. The portable imaging system as claimed in any one of the preceding claims, wherein the data management module is configured to operate independently of continuous network connectivity.

43. The portable imaging system as claimed in any one of the preceding claims, further comprising a safety control subsystem configured to interrupt operation based on predefined conditions.

44. The portable imaging system as claimed in any one of the preceding claims, further comprising a tool exchange subsystem.

45. The portable imaging system as claimed in any one of the preceding claims, wherein the tool exchange subsystem comprises a passive coupling mechanism configured to detachably couple different end-effector assemblies without the use of active actuators.

46. The portable imaging system as claimed in any one of the preceding claims, wherein the passive coupling mechanism comprises one or more alignment members and one or more latch members configured to secure the end-effector assembly.

47. The portable imaging system as claimed in any one of the preceding claims, wherein the alignment members comprise a plurality of pins configured to engage corresponding alignment channels.

48. The portable imaging system as claimed in any one of the preceding claims, wherein the passive coupling mechanism is configured to engage or disengage in response to a rotational movement of a robotic arm.

49. The portable imaging system as claimed in any one of the preceding claims, wherein the compliant mechanism of the end-effector assembly comprises one or more resilient members configured to provide controlled displacement under load.

50. The portable imaging system as claimed in any one of the preceding claims, wherein the compliant mechanism further comprising one or more guide elements configured to constrain movement of the end-effector assembly along a predefined axis.

51. The portable imaging system as claimed in any one of the preceding claims, wherein the compliant mechanism is configured to provide a predefined force threshold before displacement occurs.

52. The portable imaging system as claimed in any one of the preceding claims, further comprising a power subsystem configured to provide backup power.

53. The portable imaging system as claimed in any one of the preceding claims, further comprising a predictive maintenance module configured to monitor operational parameters of the scanning assembly.

54. The portable imaging system as claimed in any one of the preceding claims, wherein the predictive maintenance module comprises a machine learning model configured to detect deviations in operational parameters.

55. The portable imaging system as claimed in any one of the preceding claims, further comprising an audio interface configured to provide instructions to a user during scanning.

56. The portable imaging system as claimed in any one of the preceding claims, further comprising a fluid dispensing device which is configured to apply a coupling medium to the one or more body parts.

57. The portable imaging system as claimed in any one of the preceding claims, further comprising a cleaning subsystem configured to clean the one or more body parts after scanning.

58. The portable imaging system as claimed in any one of the preceding claims, wherein the cleaning subsystem comprises a cleaning end-effector configured to remove residual coupling medium.

59. The portable imaging system as claimed in any one of the preceding claims, further comprising a wheeled chassis.

60. A method for automated ultrasound examination of one or more body parts of a user by using portable imaging system as claimed in claim 1, the method comprising:positioning one or more ultrasound probes relative to the one or more body parts;acquiring ultrasound image data of the one or more body parts; controlling movement of the one or more ultrasound probes based on predetermined information relating to the one or more body parts;processing the acquired ultrasound image data; andadjusting a position and / or orientation of the one or more ultrasound probes during scanning based on feedback derived from the processed ultrasound image data.

61. The method as claimed in claim 60, wherein the step of positioning the one or more ultrasound probes comprises using one or more robotic arms having six or more degrees of freedom.

62. The method as claimed in claim 61 , wherein the step of positioning further comprising a step of moving the one or more ultrasound probes along a linear axis.

63. The method as claimed in any one of claims 60 to 62, further comprising a step of sensing force and / or contact between the one or more ultrasound probes and the one or more body parts.

64. The method as claimed in claim 63, wherein the step of sensing comprises using a multi-axis force torque sensor.

65. The method as claimed in any one of claims 60 to 64, further comprising a step of obtaining spatial information of the one or more body parts.

66. The method as claimed in claim 65, wherein the step of obtaining spatial information comprises generating a three-dimensional model or depth data.

67. The method as claimed in any one of claims 65 to 66, further comprising a step of determining an initial position and / or orientation of the one or more ultrasound probes based on the spatial information.

68. The method as claimed in any one of claims 60 to 67, wherein the step of processing comprises identifying one or more anatomical features.

69. The method as claimed in any one of claims 60 to 68, further comprising a step of adjusting the position and / or orientation of the one or more ultrasound probes based on the identified features.

70. The method as claimed in any one of claims 60 to 69, wherein the step of processing comprises determining whether image quality satisfies one or more predefined criteria.

71. The method as claimed in claim 70, further comprising a step of modifying the position and / or orientation of the one or more ultrasound probes when the criteria are not satisfied.

72. The method as claimed in any one of the preceding claims, further comprising a step of obtaining calibration data using one or more inertial measurement units.

73. The method as claimed in any one of the preceding claims, further comprising a step of compensating for structural misalignment of the portable imaging system based on the calibration data.

74. The method as claimed in any one of the preceding claims, further comprising a step of coordinating movement of two or more robotic arms to perform a scanning operation.

75. The method as claimed in any one of the preceding claims, further comprising a step of applying a coupling medium to the one or more body parts prior to acquiring ultrasound image data.

76. The method as claimed in any one of the preceding claims, further comprising a step of synchronising ultrasound image data with sensor data.

77. The method as claimed in any one of the preceding claims, further comprising a step of storing ultrasound image data and transmitting the stored data upon re-establishment of network connectivity.

78. The method as claimed in any one of the preceding claims, further comprising a step of monitoring operational parameters of the portable imaging system to detect deviations.

79. The method as claimed in any one of the preceding claims, further comprising a step of predicting maintenance requirements based on the detected deviations.

80. The method as claimed in any one of the preceding claims, further comprising a step of performing a cleaning operation on the one or more body parts after acquiring ultrasound image data.

81. A fully autonomous clinical ultrasound imaging system, comprising: a structural platform configured as a van-transportable mobile kiosk; a localized structural chassis enclosing a dedicated active cooling system and a localized edge-processing data management module, connected via internal CAN Bus, USB 3.1 , and Gigabit Ethernet pipelines, configured to execute a store-and-forward synchronization protocol to push operational data to a monitoring cloud server upon the re-establishment of network connectivity;a local historian module utilizing a hardware-level system clock pulsing at 30 Hz to time-synchronize multimodal data streams into a concatenated input tensor;a collaborative dual-robotic manipulation assembly;a multi-modal vision suite for generating occlusion-resistant volumetric depth maps;a distributed Inertial Measurement Unit (IMU) network configured to mathematically correct mechanical skews and spatial disbalance without instrument-level physical leveling;a multi-modal closed-loop sensory network for collision detection comprising a redundant network of inductive and capacitive sensors operating at a 50mm threshold;a 6-axis force torque sensor mounted exclusively on a final joint for mechanical admittance control;a safety controller configured to arrest kinetic motion if non-final joint current draw exceeds 15% for more than 50 milliseconds; anda dynamic end-effector exchange subsystem comprising a passive chassis docking station.

82. The system of claim 81 , wherein the multi-modal vision suite further comprises: A kinetic isolation gantry configured as an L-shaped top-mounted frame that is vibration-isolated from the chassis; A central dome PTZ camera, a primary 3D spatial camera mounted directly above the calculated Center of Gravity, and an auxiliary 3D spatial camera to mitigate spatial occlusion.

83. The system of claim 81, wherein the calibration module continuously evaluates IMU telemetry and automatically engages a hardware safety interlock if structural tilt exceeds a predefined threshold, locking the system in standby.

84. The system of claim 81 , further comprising a hybrid active-passive compliant end-effector assembly serving as a probe shock absorber, comprising two rigid vertical guides featuring roller bearings on pins inserted into a vertical guide cavity, and utilizing three compression springs mathematically pre-compressed to establish a rigid breakaway force threshold.

85. The system of claim 84, wherein each compression spring is geometrically constrained such that its free length divided by its mean diameter yields a slenderness ratio no greater than four (L / D <= 4), rendering the springs inherently resistant to lateral buckling independent of internal guide rails.

86. The system of claim 81, wherein the dynamic end-effector exchange subsystem utilizes a passive mechanical tool changer featuring four precision-hardened index pins that mate with four reamed alignment channels, and inverseprofile latches configured to mechanically retract an internal center plate via a 15-degree anti-clockwise robotic rotation inside the docking station located exclusively at the distal lateral extremities of a horizontal translational 7th-axis unit, without the use of active pneumatic or electromagnetic components.

87. The system of claim 81 , wherein the ultrasonic probes further comprise a wired configuration bypassing slip rings via shielded internal ducts, and a wireless configuration utilizing an isolated shielded enclosure for onboard high-frequency RF signal processing operating via high-speed WiFi or Bluetooth protocols.

88. The system of claim 81 , further comprising an autonomous clinical fluid dispenser featuring a 6-12vDC micro peristaltic pump, a perpendicular microapproach Time-of-Flight (ToF) IR sensor array, active thermal regulation maintaining fluid at exactly 40 degrees Celsius, and a cleaner end-effector comprising an integrated electromagnet configured to magnetically retrieve a high-absorption sanitization towel from an automatically opening towel bin.

89. The system of claim 81 , further comprising an autonomous hygiene and consumable replenishment subsystem comprising a sanitization sink with an internally connected system-operated hatch, integrated sterilization pans in the docking stations, and smart-refill dispensers utilizing umbilical docking ports.

90. The system of claim 81 , wherein the localized edge-processing module comprises a dual-stage Al pipeline, an anchor-free CNN for ROI extraction configured to calculate a Minimizing Displacement Error (MDE) and a detection confidence level (C_det), an RL agent for kinematic trajectory optimization configured to maximize a reward function positively correlated to C_det, and an Inverse Kinematics (IK) solver to translate spatial coordinates into joint motor commands.

91. The system of claim 90, wherein the localized edge-processing module further comprises an active audio-verbal feedback interface to autonomously issue directed verbal commands to enforce patient physiological compliance.

92. The system of claim 81, further comprising a telerobotic training subsystem featuring an operator-facing haptic cancellation module configured to ingest 6-DoF spatial coordinates from an external haptic device or mobile application via network or Bluetooth protocols, transform said coordinates into force and direction vectors cycling at a 30 Hz frequency, and apply a low-pass kinematic filter to mathematically isolate and eliminate human operator tremor frequencies from incoming manual spatial commands.

93. The system of claim 81 , wherein the data management module executes a dual digital twin architecture comprising an operational space digital twin for spatial mapping and a patient monitoring digital twin aggregating historical telemetry for longitudinal analytics.

94. The system of claim 81, wherein the data management module comprises an ESIM network gateway isolated during clinical scanning, configured to transmit anonymized predictive maintenance telemetry exclusively in asynchronous fallback mode utilizing TLS 1.3 cryptographic protocols, and wherein all localized data storage utilizes AES-256 encryption in compliance with IEC 81001-5-1 standards.

95. The system of claim 81 , further comprising a clinically isolated power architecture utilizing a medical-grade UPS configured for a millisecond-latency switchover and onboard Lithium energy storage configured for continuous safe mechanical retraction during total power loss.

96. An automated method of acoustic data acquisition, trajectory control, and predictive maintenance utilizing the system of claim 81, comprising the steps of:executing primary calibration via IMU telemetry to correct structural skew, and automatically resolving ongoing calibration drift utilizing an onboard software resolution module;coordinating a pre-scan preparation cycle wherein a first robotic arm attaches an ultrasound probe and a second robotic arm attaches a fluid dispenser to apply acoustic gel to a biological target mathematically identified via the operational space digital twin;generating volumetric depth maps via the kinetic isolation gantry; acquiring ultrasonic voxel data and comparing it against a learned normative 3D anatomical model locally on the edge-processing module;autonomously issuing directed verbal commands via the audio-verbal interface to ensure physiological compliance;calculating a Minimizing Displacement Error (MDE) alongside a detection confidence level (C_det) and translating spatial targets into joint motor commands via an Inverse Kinematics (IK) solver;generating an uncorrupted, annotated robotic ultrasound dataset within a telerobotic training subsystem by ingesting 6-DoF manual coordinates, translating said coordinates into force and direction vectors at a 30 Hz cycle synced via a hardware-level system clock to match the frame rate of the multimodal vision suite, executing said vectors on the robotic arm within a 1 / 30 second time window, and saving the timestamped vectors, 3D digital twin frames, camera feeds, and reconstructed ultrasound images to a local historian;executing a post-scan autonomous hygiene cycle wherein the second robotic arm attaches an electromagnetic cleaner to physically wipe the biological target and discard waste into an automated bin, while the first robotic arm docks the ultrasound probe into a system-operated sanitization sink;flagging data packets for review while expressly omitting the generation of a deductive medical diagnosis; andprocessing continuous hardware health-check data, kinetic current-draw deviations, and end-effector telemetric inventory data through a predictive maintenance Artificial Intelligence model.

97. The method of claim 96, wherein the reinforcement learning (RL) agent is structured as a computational tool utilizing a Deep Deterministic Policy Gradient (DDPG) algorithm governed by human-defined hyperparameters, and generated utilizing a rigorously documented dataset sourced from fully anonymized clinical repositories verified via Institutional Review Board (IRB) anonymization protocols.

98. The method of claim 96, wherein the predictive maintenance Artificial Intelligence model utilizes an Elastic Weight Consolidation (EWC) module to mathematically protect synaptic weights associated with prior spatial navigation and hardware diagnostic tasks against catastrophic forgetting using a Fisher information matrix diagonal, mathematically governed by the penalty loss function: L(0) = L_new(0) + Z (A / 2) F_i (0_i - 0*_A,i)A2

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