Wrist Orientation Research Articles

Experimental Analysis of Freehand Multi-object Selection Techniques in Virtual Reality Head-Mounted Displays

Object selection is essential in virtual reality (VR) head-mounted displays (HMDs). Prior work mainly focuses on enhancing and evaluating techniques for selecting a single object in VR, leaving a gap in the techniques for multi-object selection, a more complex but common selection scenario. To enable multi-object selection, the interaction technique should support group selection in addition to the default pointing selection mode for acquiring a single target. This composite interaction could be particularly challenging when using freehand gestural input. In this work, we present an empirical comparison of six freehand techniques, which are comprised of three mode-switching gestures (Finger Segment, Multi-Finger, and Wrist Orientation) and two group selection techniques (Cone-casting Selection and Crossing Selection) derived from prior work. Our results demonstrate the performance, user experience, and preference of each technique. The findings derive three design implications that can guide the design of freehand techniques for multi-object selection in VR HMDs.

Phase-Dependent Visual and Sensorimotor Integration of Features for Grasp Computations before and after Effector Specification.

The simple act of viewing and grasping an object involves complex sensorimotor control mechanisms that have been shown to vary as a function of multiple object and other task features such as object size, shape, weight, and wrist orientation. However, these features have been mostly studied in isolation. In contrast, given the nonlinearity of motor control, its computations require multiple features to be incorporated concurrently. Therefore, the present study tested the hypothesis that grasp computations integrate multiple task features superadditively in particular when these features are relevant for the same action phase. We asked male and female human participants to reach-to-grasp objects of different shapes and sizes with different wrist orientations. Also, we delayed the movement onset using auditory signals to specify which effector to use. Using electroencephalography and representative dissimilarity analysis to map the time course of cortical activity, we found that grasp computations formed superadditive integrated representations of grasp features during different planning phases of grasping. Shape-by-size representations and size-by-orientation representations occurred before and after effector specification, respectively, and could not be explained by single-feature models. These observations are consistent with the brain performing different preparatory, phase-specific computations; visual object analysis to identify grasp points at abstract visual levels; and downstream sensorimotor preparatory computations for reach-to-grasp trajectories. Our results suggest the brain adheres to the needs of nonlinear motor control for integration. Furthermore, they show that examining the superadditive influence of integrated representations can serve as a novel lens to map the computations underlying sensorimotor control.

Design and Analysis of VARONE a Novel Passive Upper-Limb Exercising Device

Robots have been widely investigated for active and passive rehabilitation therapy of patients with upper limb disabilities. Nevertheless, the rehabilitation assessment process is often ignored or just qualitatively performed by the physiotherapist implementing chart-based ordinal scales or observation-based measures, which tend to rely on professional experience and lack quantitative analysis. In order to objectively quantify the upper limb rehabilitation progress, this paper presents a noVel pAssive wRist motiOn assessmeNt dEvice (VARONE) having three degrees of freedom (DoFs) based on the gimbal mechanical design. VARONE implements a mechanism of three revolute passive joints with controllable passive resistance. An inertial measurement unit (IMU) sensor is used to quantify the wrist orientation and position, and an encoder module is implemented to obtain the arm positions. The proposed VARONE device can also be used in combination with the previously designed two-DoFs device NURSE (cassiNo-qUeretaro uppeR limb aSsistive dEvice) to perform multiple concurrent assessments and rehabilitation tasks. Analyses and experimental tests have been carried out to demonstrate the engineering feasibility of the intended applications of VARONE. The maximum value registered for the IMU sensor is 36.8 degrees, the minimum value registered is −32.3 degrees, and the torque range registered is around −80 and 80 Nmm. The implemented models include kinematics, statics (F.E.M.), and dynamics. Thirty healthy patients participated in an experimental validation. The experimental tests were developed with different goal-defined exercising paths that the participant had to follow.

The efficacy of different torque profiles for weight compensation of the hand.

Orthotic wrist supports will be beneficial for people with muscular weakness to keep their hand in a neutral rest position and prevent potential wrist contractures. Compensating the weight of the hands is complex since the level of support depends on both wrist and forearm orientations. To explore simplified approaches, two different weight compensation strategies (constant and linear) were compared to the theoretical ideal sinusoidal profile and no compensation in eight healthy subjects using a mechanical wrist support system. All three compensation strategies showed a significant reduction of 47-53% surface electromyography activity in the anti-gravity m. extensor carpi radialis. However, for the higher palmar flexion region, a significant increase of 44-61% in the m. flexor carpi radialis was found for all compensation strategies. No significant differences were observed between the various compensation strategies. Two conclusions can be drawn: (1) a simplified torque profile (e.g., constant or linear) for weight compensation can be considered as equally effective as the theoretically ideal sinusoidal profile and (2) even the theoretically ideal profile provides no perfect support as other factors than weight, such as passive joint impedance, most likely influence the required compensation torque for the wrist joint.

A Semiautonomous Control Strategy Based on Computer Vision for a Hand–Wrist Prosthesis

Alleviating the burden on amputees in terms of high-level control of their prosthetic devices is an open research challenge. EMG-based intention detection presents some limitations due to movement artifacts, fatigue, and stability. The integration of exteroceptive sensing can provide a valuable solution to overcome such limitations. In this paper, a novel semiautonomous control system (SCS) for wrist–hand prostheses using a computer vision system (CVS) is proposed and validated. The SCS integrates object detection, grasp selection, and wrist orientation estimation algorithms. By combining CVS with a simulated EMG-based intention detection module, the SCS guarantees reliable prosthesis control. Results show high accuracy in grasping and object classification (≥97%) at a fast frame analysis frequency (2.07 FPS). The SCS achieves an average angular estimation error ≤18° and stability ≤0.8° for the proposed application. Operative tests demonstrate the capabilities of the proposed approach to handle complex real-world scenarios and pave the way for future implementation on a real prosthetic device.

Ergonomic learning curves on gynecological laparoendoscopic single-site (LESS) surgery

BackgroundFew previous studies have introduced general techniques to overcome the “chopstick effect” in laparoendoscopic single-site surgery (LESS). We aim to investigate and highlight the key ergonomic methodologies for gynaecologic LESS based on the surgeon’s hands-on performance.MethodsThe first author surgeon A reviewed and analyzed the LESS procedures performed by herself and how she taught surgeon B from January 2021 to April 2022. The procedures were classified based on technical difficulty and learning periods, and the hands-on technical skills of LESS module were evaluated.ResultsSurgeon A conducted 580 LESS procedures, which were divided into the novice (n = 48) and intermediate (n = 33) periods, and the remaining cases were included in the routine period. We formed a special ergonomic LESS operating methodology: Maintain good LESS laparoscopic spatial sensation, keep hand-eye coordination, well cooperation between the main surgeon and the assistant; Experienced multiport laparoscopy surgery (MPS) skills, improve basic LESS technique: grasp, lift, transfer, place, blunt separating, coagulation and cutting. Coordination location, orientation, movements, and flexion or extension of shoulders, arms, elbow, wrist and finger joints; Maintain strength, tension and ambidexterity postures with joint and muscular efforts to control instruments. Surgeon B learned the above experiences by performing 39 LESS procedures under the guidance of surgeon A.ConclusionThis educational research sheds light on the common challenges faced in LESS and presents the importance of ergonomic hands-on performance skills in improving surgical outcomes, which could serve as a guide for future training and education in LESS.

Synthetic Smartwatch IMU Data Generation from In-the-wild ASL Videos

The scarcity of training data available for IMUs in wearables poses a serious challenge for IMU-based American Sign Language (ASL) recognition. In this paper, we ask the following question: can we "translate" the large number of publicly available, in-the-wild ASL videos to their corresponding IMU data? We answer this question by presenting a video to IMU translation framework (Vi2IMU) that takes as input user videos and estimates the IMU acceleration and gyro from the perspective of user's wrist. Vi2IMU consists of two modules, a wrist orientation estimation module that accounts for wrist rotations by carefully incorporating hand joint positions, and an acceleration and gyro prediction module, that leverages the orientation for transformation while capturing the contributions of hand movements and shape to produce realistic wrist acceleration and gyro data. We evaluate Vi2IMU by translating publicly available ASL videos to their corresponding wrist IMU data and train a gesture recognition model purely using the translated data. Our results show that the model using translated data performs reasonably well compared to the same model trained using measured IMU data.

Complementary contribution of the medial and lateral human parietal cortex to grasping: a repetitive TMS study.

The dexterous control of our grasping actions relies on the cooperative activation of many brain areas. In the parietal lobe, 2 grasp-related areas collaborate to orchestrate an accurate grasping action: dorsolateral area AIP and dorsomedial area V6A. Single-cell recordings in monkeys and fMRI studies in humans have suggested that both these areas specify grip aperture and wrist orientation, but encode these grasping parameters differently, depending on the context. To elucidate the causal role of phAIP and hV6A, we stimulated these areas, while participants were performing grasping actions (unperturbed grasping). rTMS over phAIP impaired the wrist orientation process, whereas stimulation over hV6A impaired grip aperture encoding. In a small percentage of trials, an unexpected reprogramming of grip aperture or wrist orientation was required (perturbed grasping). In these cases, rTMS over hV6A or over phAIP impaired reprogramming of both grip aperture and wrist orientation. These results represent the first direct demonstration of a different encoding of grasping parameters by 2 grasp-related parietal areas.

Movement preferences of the wrist and forearm during activities of daily living

BackgroundDuring activities of daily living, the main degrees of freedom of the forearm and wrist—forearm pronation-supination (PS), wrist flexion-extension (FE), and wrist radial-ulnar deviation (RUD)—combine seamlessly to allow the hand to engage with and manipulate objects in our environment. Yet the combined behavior of these three degrees of freedom is relatively unknown. PurposeTo provide a characterization of natural forearm and wrist kinematics (joint configuration, movement direction, and speed) during activities of daily living. Study designThis is a descriptive cross-sectional study. MethodsTen healthy subjects performed 24 activities of daily living chosen to represent a wide variety of activities, while we measured their PS, FE, and RUD angles using electromagnetic motion capture. The orientation of the forearm and wrist was represented in the three-dimensional “configuration space” spanned by PS, FE, and RUD. From the time course of forearm and wrist orientation in configuration space, we extracted three-dimensional distributions of joint configuration, movement direction, and speed. ResultsMost joint configurations were focused in a relatively small area: subjects spent roughly 50% of the time in the central 20% of their functional range of motion. Some movement directions were significantly more common than others (p < 0.001); in particular, the direction of the dart-thrower's motion (DTM) was about three times more common than motion perpendicular to it. Most movements were slow: the likelihood of moving at increasing speeds dropped off exponentially. Interestingly, the most common high-speed motion combined the DTM with a twist from pronation to supination. As this motion allows one to pick up an object in front of one's body and bring it to the head, it is essential for self-care. Thus, although many activities of daily living follow the DTM without significant forearm rotation, the greatest importance of the DTM may lie in its combination with forearm rotation. ConclusionsDespite the wide variety of activities, we found evidence of preferred movement behavior, and this behavior showed significant coupling between the wrist and forearm.

Step-by-step optimisation of robotic-assisted radical prostatectomy using augmented reality

ABSTRACTIntroduction:Surgical training will be complemented by digitalisation, as the COVID 19 pandemic continues (1). Proximie is an augmented reality (AR) platform that can display up to 4 native camera views, with live or semi live telementoring. It can optimise ergonomics of the surgeon at the console (2), and robotic instrument orientation. We describe the utilisation of Proximie as a step-by-step guide in a robotic assisted radical prostatectomy (RARP).Surgical Technique:Author V. P. performed a transperitoneal multiport da Vinci Xi RARP with the Proximie platform: a laptop computer, multiple HD webcams, microphones and speakers. Using an HDMI cable to the Intuitive Surgical tower, output display from the console and an additional laparoscopic tower is shown. Each webcam was mounted to the side armrests of the console, directed at the surgeon's hands. An independent ‘drop in’ laparoscope via an additional 5mm left upper quadrant port was utilised. Observers can visualise the AR platform's recordings on a laptop and/or smartphone. A PTZ (pan-tilt-zoom) camera can capture the operating room, bedside assistant, ports and patient position. Our video demonstrates three of four camera views for posture, forearm, wrist, hand, and finger orientation, relative to the translated robotic steps. A pincer grasp of the endowrist manipulator during anastomosis allows optimal robotic wrist rotation. The second laparoscopic camera view demonstrated intracorporeal angles of robotic arm and bedside assistant's instrument position for critical steps such as nerve sparing and anastomosis (3). The console time was 100 minutes, no intraoperative complications, or delay in image transmission occurred with utilising the platform.Considerations:An AR platform can create deeper learning for RARP in real time or recorded sessions. Two-way verbal and visual communication with ability to annotate on screen, allows long distance mentoring. The platform's utility can be accessed in anywhere, to project surgeons beyond their immediate environment. This allows for democratisation of access to high volume institutions and their evolution of techniques (4), to assist patients globally. Potential developments are artificial intelligence (AI) networks analysing repository of such recorded data, to identify intraoperative hand motion and robotic instrument tracking. AR is a pertinent building block to enhance robotic training, skill dissemination, precision medicine (5) and surgery overall.

Posture-Dependent Variability in Wrist Ballistocardiogram-Photoplethysmogram Pulse Transit Time: Implication to Cuff-Less Blood Pressure Tracking.

Toward the ultimate goal of robust cuff-less blood pressure (BP) tracking with wrist wearables against postural changes, the goal of this work was to investigate posture-dependent variability in pulse transit time (PTT) measured with ballistocardiogram (BCG) and photoplethysmogram (PPG) signal pair at the wrist. BCG and PPG signals were acquired from 25 subjects under the combination of 3 body (standing, sitting, and supine) and 3 arm (vertical in head-to-foot direction, placed on the chest, and holding a shoulder) postures. PTT was computed as the time interval between the BCG J wave and the PPG foot, and the impact of the 9 postures on PTT was analyzed by invoking an array of possible physical mechanisms. Our work suggests that (i) wrist BCG-PPG PTT is consistent under standing and sitting postures with vertically held arms; and (ii) changes in wrist orientation and height as well as restrictions in body and arm movement may alter wrist BCG-PPG PTT via distortions in the wrist BCG and PPG waveforms. The results indicate that wrist BCG-PPG PTT varies with respect to postures even when BP remains constant. The potential of cuff-less BP tracking via wrist BCG-PPG PTT demonstrated under standing posture with arms vertically down in the head-to-foot direction may not generalize to other body and arm postures. Understanding the physical mechanisms responsible for posture-induced BCG-PPG PTT variability may increase the versatility of the wrist BCG for cuff-less BP tracking.

An Electro-Oculogram Based Vision System for Grasp Assistive Devices-A Proof of Concept Study.

Humans typically fixate on objects before moving their arm to grasp the object. Patients with ALS disorder can also select the object with their intact eye movement, but are unable to move their limb due to the loss of voluntary muscle control. Though several research works have already achieved success in generating the correct grasp type from their brain measurement, we are still searching for fine controll over an object with a grasp assistive device (orthosis/exoskeleton/robotic arm). Object orientation and object width are two important parameters for controlling the wrist angle and the grasp aperture of the assistive device to replicate a human-like stable grasp. Vision systems are already evolved to measure the geometrical attributes of the object to control the grasp with a prosthetic hand. However, most of the existing vision systems are integrated with electromyography and require some amount of voluntary muscle movement to control the vision system. Due to that reason, those systems are not beneficial for the users with brain-controlled assistive devices. Here, we implemented a vision system which can be controlled through the human gaze. We measured the vertical and horizontal electrooculogram signals and controlled the pan and tilt of a cap-mounted webcam to keep the object of interest in focus and at the centre of the picture. A simple ‘signature’ extraction procedure was also utilized to reduce the algorithmic complexity and system storage capacity. The developed device has been tested with ten healthy participants. We approximated the object orientation and the size of the object and determined an appropriate wrist orientation angle and the grasp aperture size within 22 ms. The combined accuracy exceeded 75%. The integration of the proposed system with the brain-controlled grasp assistive device and increasing the number of grasps can offer more natural manoeuvring in grasp for ALS patients.

Two-stage grasp strategy combining CNN-based classification and adaptive detection on a flexible hand

Robotic autonomous grasping of food-related objects requires a nondestructive and safe grasp system for picking up various objects. A novel underactuated flexible hand consisting of a variable palm and four soft fingers is designed and manufactured to enhance the grasp space and deformability during interaction with unknown objects. A position deviation formulation is fitted to estimate the free bend deformation of soft fingers approximately through finite element analysis. A modular convolutional neural network is presented to identify the grasp directions, shape features and anticipated input pressure levels of novel objects for achieving multitarget classification. A vision-based adaptive detection method is proposed to obtain an accurate wrist orientation and the best grasp candidate by using two means of grasp planning (i.e. cross grasp planning and equidistant optimal grasp planning). A two-stage grasp strategy combining the classification and detection methods is developed as an effective solution to estimate the grasp configuration accurately. Results show that our flexible hand achieves 91.1% success rate in a physical grasp experiment on a UR robot, thereby demonstrating the reliability and adaptability of our grasp approach. The target object can be identified and detected within 0.263 s, which indicates the suitability of our approach in real-time applications.

Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.

Background: Near-falls such as a trip, slip, stumble, or misstep involve a loss of balance (LOB) that does not result in a fall, occur more frequently than actual falls, and are associated with an increased fall risk. To date, studies have largely involved detection of simulated laboratory LOBs using wearable devices in young adults. Data on the detection of and kinematics of naturally occurring LOBs in people at high risk of falling are lacking. This may provide a new way to identify older adults at high risk for falls. We aimed to explore key body kinematics underlying real-world trips in at-fall risk community dwelling older adults wearing inertial measurement units (IMU).Methods: Five community-dwelling older adults with a history of falls who reported trips during the study period participated. They wore a voice recorder and 4 IMUs mounted on feet, lower back and wrist for two consecutive weeks to provide a record of the context and timing of LOB events. Sensor data prior to time-stamped voice recording of a trip were processed in order to visually identify unusual foot trajectories and lower back and arm orientations. Then, data of feet, lower back and wrist position and orientation were combined to create a three-dimensional animation representing the estimated body motion during the noted time segments in order to corroborate the occurrence of a trip. Events reported as a trip by the participant and identified as a trip by a researcher, blinded to voice recordings description, were included in the final analysis.Results: A total of 18 trips obtained from five participants were analyzed. Twelve trips occurred at home, three outside and for three the location was not reported. Trips were identified in the sensor data by observing (1) additional peaks to the typical foot velocity signal during swing phase; (2) increased velocity of the contralateral foot and (3) sharp changes in lower back pitch angles.Conclusions: Our approach demonstrates the feasibility of identifying and studying the mechanisms and context underlying trip-related LOBs in at-fall risk older adults during real world activities.

Hierarchical Action Encoding Within the Human Brain.

Humans are able to interact with objects with extreme flexibility. To achieve this ability, the brain does not only control specific muscular patterns, but it also needs to represent the abstract goal of an action, irrespective of its implementation. It is debated, however, how abstract action goals are implemented in the brain. To address this question, we used multivariate pattern analysis of functional magnetic resonance imaging data. Human participants performed grasping actions (precision grip, whole hand grip) with two different wrist orientations (canonical, rotated), using either the left or right hand. This design permitted to investigate a hierarchical organization consisting of three levels of abstraction: 1) "concrete action" encoding; 2) "effector-dependent goal" encoding (invariant to wrist orientation); and 3) "effector-independent goal" encoding (invariant to effector and wrist orientation). We found that motor cortices hosted joint encoding of concrete actions and of effector-dependent goals, while the parietal lobe housed a convergence of all three representations, comprising action goals within and across effectors. The left lateral occipito-temporal cortex showed effector-independent goal encoding, but no convergence across the three levels of representation. Our results support a hierarchical organization of action encoding, shedding light on the neural substrates supporting the extraordinary flexibility of human hand behavior.

Alarm device for self-tracking of progression during wrist rehabilitation

This study aims to design an alarming device for patients requiring wrist rehabilitation. Wrist injury due to accident, sports, stroke, and prolonged hand immobilization often requires physical therapy for rehabilitation to reduce pain, improve range of motion (ROM), and regain strength and function. Physical therapists use a goniometer to measure ROM. Although systematic treatment for wrist rehabilitation is physical therapy, current researchers are seeking an alternative and self-educative procedure based on engineering principles. This paper proposes a self-educative assessment and progress tracking design by exploiting an engineering design. This design is aided by a microcontroller, interfaced with sensors and display unit to measure wrist orientation of patients. The sensors measure the ROM of patients. This system uses a buzzer as an alarm tool for the patients during therapy. If the patients have achieved targeted movements, a beep sound would be produced to notify the patients. Thus, patients will be attentive in the treatment and motivated to proceed with the therapy. Visualization of the ROM through the display unit and alarm signal acts as an educating platform. The prototype was administered on five subjects with reduced ROM in wrist. Results showed that the proposed design increases ROM and self-educate the patients with wrist injuries (p&lt;0.05).

Reducing the effect of wrist variation on pattern recognition of Myoelectric Hand Prostheses Control through Dynamic Time Warping

For upper limb prostheses, research carried out earlier mainly focused on increasing the classification accuracy of the hand movements; but there exist a little work done on factors affecting it in real-time control such as wrist variation. Amputees with functional wrist use their prostheses in multiple wrist positions. Since the Electromyography (EMG) data is taken while the subject is performing the motion in different wrist position, it can degrade the performance of the Pattern Recognition (PR) system. In this work, a wrist independent PR scheme has been developed. In this regard, Dynamic Time Warping (DTW) is used to overcome the effects due to wrist variation. The performance of the DTW scheme as a PR system is validated using two training methods; with classification accuracy as a performance measure on data taken from the database of ten intact subjects for six hand motions carried out at three different wrist orientations. On the database, an average classification accuracy of about 93.3% was obtained while trained using EMG data from all possible wrist positions. The effectiveness of the method is demonstrated in terms of classification accuracy and processing time when compared with the Time-domain power spectral descriptors (TD-PSD) method which outperformed other methods in the literature for reducing the impact of wrist variation on EMG based PR. The results show that the DTW can be a computationally cheap and accurate PR system for real-time hand movement classification.

Analyzing the Trade-Off Between Training Session Time and Performance in Myoelectric Hand Gesture Recognition During Upper Limb Movement.

Although remarkable improvements have been made, the natural control of hand prostheses in everyday life is still challenging. Changes in limb position can considerably affect the robustness of pattern recognition-based myoelectric control systems, even if various strategies were proposed to mitigate this effect. In this paper, we investigate the possibility of selecting a set of training movements that is robust to limb position change, performing a trade-off between training time and accuracy. Four able-bodied subjects were recorded while following a training protocol for myoelectric hand prostheses control. The protocol is composed of 210 combinations of arm positions, forearm orientations, wrist orientations and hand grasps. To the best of our knowledge, it is among the most complete including changes in limb positions. A training reduction paradigm was used to select subsets of training movements from a group of subjects that were tested on the left-out subject's data. The results show that a reduced training set (30 to 50 movements) allows a substantial reduction of the training time while maintaining reasonable performance, and that the trade-off between performance and training time appears to depend on the chosen classifier. Although further improvements can be made, the results show that properly selected training sets can be a viable strategy to reduce the training time while maximizing the performance of the classifier against variations in limb position.

Development and Evaluation of a Novel Passive Wrist Bilateral Rehabilitation Device paired with Virtual Reality: A Feasibility Study.

This paper introduces a novel passive wrist bilateral rehabilitation device coupled with a new Virtual Reality (VR) platform. This is the first work to have adapted three-link coaxial spherical parallel manipulator (SPM) to wrist rehabilitation. The device comprises a coaxial SPM and cross-connected cable system. The coaxial SPM facilitates 3 degrees of freedom (DOFs) spherical wrist orientation and singularity-free motion within its workspace. The cross-connected cable system enables bilateral symmetrical exercises in passive mode training. A VR platform with activities of daily living (ADL) task was developed and coupled with the device to increase the adherence of the users to the device. Experiments were conducted with fifteen healthy right-handed individuals with no history of wrist or hand injury to evaluate the feasibility of the system for providing passive bilateral training as well as the effectiveness of the VR platform. Subjects were asked to use their right arms to move the left arms passively through the device to perform four wrist movements, flexion, extension, radial deviation, and ulnar deviation. EMG activations on the left arm were observed when the right arm passively moved the left arm. The results showed that the device was capable of inducing the muscle activation of the left arm and the VR platform increased the motivation to continue the exercises. This demonstrates that this study can serve as the fundamental for larger clinical trials.

A new radiographic view of the scaphotrapeziotrapezoid joint-a cadaveric study.

The scaphotrapeziotrapezoid joint (STTJ) has a complex osseous and ligamentous anatomy. Precise radiographic assessment is paramount when assessing osteoarthritic, post-traumatic, or post-operative patients. There has been no described technique to image the STTJ without any wrist movement, unobscured by the rest of the carpus. The aim of this study was to define an optimal radiographic method to assess the STTJ while maintaining the wrist in neutral position. Computer tomography 3-D reconstructions of three uninjured wrists were initially used to determine an approximate beam angle. Serial radiographs of 12 cadaveric wrists were taken. The forearms were positioned in varying degrees of pronation and supination. The beam angle was concurrently adjusted to varying degrees of caudal tilt. From the images obtained, we assessed if the adjacent carpus obscured the view of the STTJ. Optimal STTJ imaging was in the semi-pronated wrist position with the X-ray beam tilted caudal. We found that the STTJ was best visualized at 48° supination from a fully pronated wrist and a caudal beam angle of 22°. The described wrist and beam orientation can aid in achieving an unobstructed view of the STTJ with little technical effort. This can aid in imaging ambulatory patients where symptoms prevent using other imaging techniques as well as patients in the operating room where imaging timing can be critical.