Ankle dorsiflexion assistance of patients with foot drop using a powered ankle-foot orthosis to improve the gait asymmetry.

BACKGROUND: Foot drop is a neuromuscular disorder that causes abnormal gait patterns. This study developed a pneumatically powered ankle-foot orthosis (AFO) to improve the gait patterns of patients with foot drop. We hypothesized that providing unilateral ankle dorsiflexion assistance during the swing phase would improve the kinematics and spatiotemporal gait parameters of such patients. Accordingly, this study aims to examine the efficacy of the proposed assistance system using a strategy for joint kinematics and spatiotemporal gait parameters (stride length, swing velocity, and stance phase ratio). The analysis results are expected to provide knowledge for better design and control of AFOs in patients with foot drop. METHOD: Ten foot drop patients with hemiparesis (54.8 y ± 14.1 y) were fitted with a custom AFO with an adjustable calf brace and portable air compressor for ankle dorsiflexion assistance in the gait cycle during the swing phase. All subjects walked under two different conditions without extensive practice: (1) barefoot and (2) wearing a powered AFO. Under each condition, the patients walked back and forth on a 9-m track with ten laps of level ground under the supervision of licensed physical therapists. The lower-limb joint and trunk kinematics were acquired using 12 motion-capture cameras. RESULTS: We found that kinematic asymmetry decreased in the three lower-limb joints after ankle dorsiflexion assistance during the swing phase. The average ankle-joint angle increased after using the AFO during the entire gait cycle. Similarly, the knee-joint angle showed a slight increase while using the AFO, leading to a significantly decreased standard deviation within patients. Conversely, the hip-joint angle showed no significant improvements with assistance. While several patients exhibited noticeably lower levels of asymmetry, no significant changes were observed in the average asymmetry of the swing velocity difference between the affected and unaffected sides while using the AFO. CONCLUSION: We experimentally validated that ankle dorsiflexion assistance during the swing phase temporarily improves gait asymmetry in foot-drop patients. The experimental results also prove the efficacy of the developed AFO for gait assistance in foot-drop patients.

Gait Analysis Accuracy Difference with Different Dimensions of Flexible Capacitance Sensors.

Stroke causes neurological pathologies, including gait pathologies, which are diagnosed by gait analysis. However, existing gait analysis devices are difficult to use in situ or are disrupted by external conditions. To overcome these drawbacks, a flexible capacitance sensor was developed in this study. To date, a performance comparison of flexible sensors with different dimensions has not been carried out. The aim of this study was to provide optimized sensor dimension information for gait analysis. To accomplish this, sensors with seven different dimensions were fabricated. The dimensions of the sensors were based on the average body size and movement range of 20- to 59-year-old adults. The sensors were characterized by 100 oscillations. The minimum hysteresis error was 8%. After that, four subjects were equipped with the sensor and walked on a treadmill at a speed of 3.6 km/h. All walking processes were filmed at 50 fps and analyzed in Kinovea. The RMS error was calculated using the same frame rate of the video and the sampling rate of the signal from the sensor. The smallest RMS error between the sensor data and the ankle angle was 3.13° using the 49 × 8 mm sensor. In this study, we confirm the dimensions of the sensor with the highest gait analysis accuracy; therefore, the results can be used to make decisions regarding sensor dimensions.

Real-Time Human Action Recognition with a Low-Cost RGB Camera and Mobile Robot Platform.

Human action recognition is an important research area in the field of computer vision that can be applied in surveillance, assisted living, and robotic systems interacting with people. Although various approaches have been widely used, recent studies have mainly focused on deep-learning networks using Kinect camera that can easily generate data on skeleton joints using depth data, and have achieved satisfactory performances. However, their models are deep and complex to achieve a higher recognition score; therefore, they cannot be applied to a mobile robot platform using a Kinect camera. To overcome these limitations, we suggest a method to classify human actions in real-time using a single RGB camera, which can be applied to the mobile robot platform as well. We integrated two open-source libraries, i.e., OpenPose and 3D-baseline, to extract skeleton joints on RGB images, and classified the actions using convolutional neural networks. Finally, we set up the mobile robot platform including an NVIDIA JETSON XAVIER embedded board and tracking algorithm to monitor a person continuously. We achieved an accuracy of 70% on the NTU-RGBD training dataset, and the whole process was performed on an average of 15 frames per second (FPS) on an embedded board system.

Research on Patient Satisfaction of Robotic Telerounding: A Pilot Study in a Korean Population.

OBJECTIVES: To evaluate the efficacy and functionality of robotic telerounding among Korean patients using the RP-7 robot system and a questionnaire survey comparing the results of robotic telerounding and standard rounding in Korean patients. METHODS: A total of 40 patients who underwent urologic minimally invasive video-assisted minilaparotomy surgery, laparoscopic and robotic surgery, and endoscopic surgery were recruited. The patients were divided into 2 groups - telerounding (20) and standard rounding (20) - and underwent robotic telerounding and standard rounding. We assessed the patients using a 24-item questionnaire to evaluate the efficacy and functionality of their hospital care. RESULTS: The hospital factors such as self-rated health, assistance, and pain control scores showed no statistically significant differences between groups. Patient satisfaction showed a statistically significant difference in MD confidence, medical communication, explanation understanding, explanation satisfaction, mutual communication, and mutual response. In the telerounding group, participants were satisfied with the audio and video qualities and believed that the robotic telerounding provided better care, and 85% of patients preferred telerounding in the absence of the attending physician. CONCLUSION: Robotic telerounding can provide efficient and cost-effective medical rounding by reducing inconvenience and labor cost with greater patient satisfaction with postoperative care. However, there is no statistically significant difference in the hospital factors and postoperative morbidity. In addition, the patients doubted that the robotic telerounding could replace standard rounding due to the Eastern culture.

Indenter study: associations between prostate elasticity and lower urinary tract symptoms.

OBJECTIVE: To investigate the associations between prostate elasticity and lower urinary tract symptoms (LUTS). METHODS: From August 2009 to December 2009, 48 patients with no history of neoadjuvant therapy or previous prostate surgery who underwent robot-assisted radical prostatectomy were included in this study. A novel palpation system was used to measure the tissue elasticity of the prostate specimens. The elasticity of the prostate was defined as the mean elastic modulus (kilopascals [kPa]) of 21 sites from the posterior surface of prostate. All patients completed an International Prostate Symptoms Score questionnaire before surgery, and LUTS was defined as an International Prostate Symptoms Score total of ≥8. Significant voiding symptoms were identified by a score of ≥5 on the basis of patient responses to 4 questions (Q1, Q3, Q5, and Q6), and storage symptoms were identified by a score ≥4 on the basis of patient responses to 3 questions (Q2, Q4, and Q7). RESULTS: The median elastic modulus of the prostate was 20.8 kPa (interquartile range 15.6-22.9), and the LUTS incidences and voiding symptoms were significantly higher in patients with an elastic modulus >20 kPa. The multivariate logistic regression results indicated that a higher elastic modulus (as a continuous variable) was independently associated with voiding symptoms (odds ratio 1.18, P = .038) after controlling for age and prostate volume. However, the elastic modulus was not independently associated with LUTS or storage symptoms. CONCLUSION: Patients with greater prostate stiffness are more likely to develop LUTS. Specifically, prostate elasticity was independently associated with voiding symptoms.

Robotic system with sweeping palpation and needle biopsy for prostate cancer diagnosis.

BACKGROUND: Early diagnosis of prostate cancers can be of major benefit to patients because, combined with proper treatments, it can increase the survival rate of patients. MATERIALS AND METHODS: A new device is described that can be used to increase diagnostic accuracy and decrease complications during the examination of prostate diseases. This device is designed to perform a palpation examination and needle biopsy together on prostate tissue. Ex-vivo experiments were conducted on human prostate and tissue phantoms. RESULTS: Experimental results show that the device can be used to localize hard tissues. To remove experimental artifacts, a procedure is suggested to identify the abnormal tissue regions using FEM-based-mechanical-property-characterization and the abnormal regions obtained by analysis were compared with information from pathology. These results show a high specificity (81.8%) and PPV (60.0%) for the detection of prostate cancer. CONCLUSIONS: This system can be applied to detect hard materials such as tumor and malignant tissue.

Local property characterization of prostate glands using inhomogeneous modeling based on tumor volume and location analysis.

Mechanical property characterization of prostate tumors can enhance the results obtained by palpation by providing quantitative and precise diagnostic information to surgeons. The multi-focal characteristics of prostate tumors cause inhomogeneity and local property variance in the prostate glands, which is one reason for inaccurate property characterizations of the tumors. Therefore, biomechanical models should include inhomogeneity and local property variance by taking into consideration the anatomical information (location and volume) of the tumors. We developed six inhomogeneous local prostate models using the finite element method, which takes into account the location and volume information of prostate tumors. The models were divided into six different sections: lateral apex, lateral mid, lateral base, medial apex, medial mid and medial base tumors. Information on the location and volume of prostate tumors was obtained using pathological analysis. The mechanical properties of prostate tumors were estimated using the developed model simulation and the ex vivo indentation experiment results from the human resected prostates. The results showed that the mean elastic moduli of the normal and tumoral regions were 14.7 and 41.6 kPa, respectively. Our models provided more reliable estimates of the elastic moduli than the conventionally used Hertz-Sneddon model, and the results from our model were more closely correlated with previous studies due to the inclusion of the anatomical information via inhomogeneous modeling. These six local models provide baseline property criteria for the diagnosis and localization of prostate tumors using the optimized elastic moduli of normal prostate tissues.

Robotic palpation and mechanical property characterization for abnormal tissue localization.

Palpation is an intuitive examination procedure in which the kinesthetic and tactile sensations of the physician are used. Although it has been widely used to detect and localize diseased tissues in many clinical fields, the procedure is subjective and dependent on the experience of the individual physician. Palpation results and biomechanics-based mechanical property characterization are possible solutions that can enable the acquisition of objective and quantitative information on abnormal tissue localization during diagnosis and surgery. This paper presents an integrated approach for robotic palpation combined with biomechanical soft tissue characterization. In particular, we propose a new palpation method that is inspired by the actual finger motions that occur during palpation procedures. To validate the proposed method, robotic palpation experiments on silicone soft tissue phantoms with embedded hard inclusions were performed and the force responses of the phantoms were measured using a robotic palpation system. Furthermore, we carried out a numerical analysis, simulating the experiments and estimating the objective and quantitative properties of the tissues. The results indicate that the proposed approach can differentiate diseased tissue from normal tissue and can characterize the mechanical information of diseased tissue, which means that this method can be applied as a means of abnormality localization to diagnose prostate cancers.

Palpation device for the identification of kidney and bladder cancer: a pilot study.

PURPOSE: To determine the ability of a novel palpation device to differentiate between benign and malignant tissues of the kidney and bladder by measuring tissue elasticity. MATERIALS AND METHODS: A novel palpation device was developed, mainly composed of a micromotor, a linear position sensor, a force transducer, and a hemisphere tip and cylindrical body probe. Motion calibration as well as performance validation was done. The tissue elasticity of both benign and malignant tissues of the kidney and bladder was measured using this device. A single investigator performed the ex-vivo palpation experiment in twelve kidneys and four bladder specimens. Malignant tissues were made available from partial nephrectomy specimens and radical cystectomy specimens. Palpations for benign renal parenchyma tissue were carried out on nephroureterectomy specimens while non-involved areas in the radical cystectomy specimens were used for benign bladder samples. Elastic modulus (Young's modulus) of tissues was estimated using the Hertz-Sneddon equation from the experimental results. These were then compared using a t-test for independent samples. RESULTS: Renal cell carcinoma tissues appear to be softer than normal kidney tissues, whereas tissues from urothelial carcinoma of the bladder appear to be harder than normal bladder tissues. The results from renal cell carcinoma differed significantly from those of normal kidney tissues (p=0.002), as did urothelial carcinoma of the bladder from normal bladder tissues (p=0.003). CONCLUSION: Our novel palpation device can potentially differentiate between malignant and benign kidney and bladder tissues. Further studies are necessary to verify our results and define its true clinical utility.

Robotic palpation-based mechanical property mapping for diagnosis of prostate cancer.

PURPOSE: The aim of this study was to estimate the mechanical properties (elasticity) of normal and cancer prostate tissues and to develop a tissue elasticity map for the diagnosis and localization of prostate cancer. MATERIALS AND METHODS: A total of 735 sites from 35 radical prostatectomy specimens were used in the experiments using a robotic palpation system, and the elasticities of the specimens were estimated by a tissue characterization algorithm. The estimated elasticities from 21 regions were separated into normal and cancer tissues using the pathological information, and a tissue elasticity map was developed using numerical functions and a nonlinear surface-fitting method. RESULTS: The mean elastic moduli of the normal and cancer tissues were 15.25 ± 5.88 and 28.80 ± 11.20 kPa, respectively. The base region had the highest elasticity, followed by the medial and apex regions. These results demonstrated the ability to separate the cancer tissue from the normal tissue based on its elastic modulus. The tissue elasticity mapping was carried out using the estimated elasticity and nonlinear surface fitting. The proposed map showed the elasticity and was used to estimate the elastic modulus of the prostate at any given region. CONCLUSION: Tissue elasticity may be an important indicator of prostate cancer because the pathologic changes alter the tissue properties, including cell integrity and intercellular matrix. This work provides quantitative and objective information for the diagnosis of prostate cancer. In addition, these results may have implications for the localization of prostate cancers.

Mechanical property characterization of prostate cancer using a minimally motorized indenter in an ex vivo indentation experiment.

OBJECTIVES: To measure the mechanical property of prostatic tissues using a minimally motorized indenter and to determine whether measurable differences in mechanical property exist between cancerous and noncancerous tissues in an ex vivo experiment. METHODS: A total of 552 sites from 46 prostate specimens taken during radical prostatectomy underwent an indentation experiment with a minimally motorized indenter, and the elastic modulus (Young's modulus) of the tissue was estimated. RESULTS: The mean elastic modulus of the regions containing cancer and noncancer was 24.1 ± 14.5 and 17.0 ± 9.0 kPa, respectively. In the noncancerous regions, the prostate was separated into 5 parts according to the post hoc test for comparing the elastic modulus between the 2 groups: part 1, lateral apex; part 2, medial apex; part 3, lateral-mid; part 4, lateral base; and part 5, medial-mid and medial base. In the regions containing cancer tissue, the prostate was also separated into 5 parts: part 1, lateral apex and medial apex; part 2, lateral-mid; part 3, lateral base; part 4, medial base; and part 5, medial-mid. The elastic modulus was greater in the tissue with a Gleason score of 8 than in the other tissue. The elastic modulus was significantly greater in the tissue with a tumor volume >5 cm(3) than in the other tissue. CONCLUSIONS: We determined the elastic moduli of prostatic tissue as a quantitative and objective parameter according to the regions of the prostate, the presence of cancerous tissue, the tumor volume, and the Gleason score.

Measurement and characterization of soft tissue behavior with surface deformation and force response under large deformations.

Soft tissue characterization with the inverse finite element method (FEM) optimization algorithm plays an important role in developing a physical model for medical simulations. However, tissue characterization that takes into account comprehensive boundary conditions for large deformations remains a challenge due to computational complexities and a lack of experimental data. In this study, soft tissue experiments on porcine livers were performed to measure the surface deformation and force response of soft tissues resulting from indentation loading depending on various indentation depths and two different tip shapes. Measurements were carried out with a three-dimensional (3D) optical system and a force transducer. Using the surface deformation and force response results, we estimated the maximum radius of influence, which can be utilized to determine the minimal required soft tissue model size for the FEM simulation. Considering the influence of the boundary conditions, the model was designed and integrated into an inverse FEM optimization algorithm to estimate the model parameters. The mechanical behavior of large deformations was characterized with FE modeling via hyperelastic and linear viscoelastic models.

Inclusion detection with haptic-palpation system for medical telediagnosis.

Detection of abnormalities in subcutaneous tissue is an important issue in medical diagnosis. Surgeons palpate this type of tissue to perceive pathologies through haptic sensation. This paper presents the framework of a real-time haptic-palpation system with inclusion detection to manipulate biological soft tissues and perceive their structures and material properties non-invasively. A user with a haptic device guides a robotic manipulator to perform palpation tasks and can detect the location of inclusions inside a soft medium (silicone-molded tissue phantom). For the objective measurement of the depth of the inclusion, a finite element (FE) model was developed to predict the reaction forces for various inclusion depths. The methods presented in this paper can be applied to the early detection of prostate cancer or breast cancer in telediagnosis.

Graphic and haptic modelling of the oesophagus for VR-based medical simulation.

BACKGROUND: Medical simulators with vision and haptic feedback have been applied to many medical procedures in recent years, due to their safe and repetitive nature for training. Among the many technical components of the simulators, realistic and interactive organ modelling stands out as a key issue for judging the fidelity of the simulation. This paper describes the modelling of an oesophagus for a real-time laparoscopic surgical simulator. METHODS: For realistic simulation, organ deformation and tissue cutting in the oesophagus are implemented with geometric organ models segmented from the Visible Human Dataset. The tissue mechanical parameters were obtained from in vivo animal experiments and integrated with graphic and haptic devices into the laparoscopic surgical simulation system inside an abdominal mannequin. RESULTS: This platform can be used to demonstrate deformation and incision of the oesophagus by surgical instruments, where the user can haptically interact with the virtual soft tissues and simultaneously see the corresponding organ deformation on the visual display. CONCLUSIONS: Current laparoscopic surgical training has been transformed from the traditional apprenticeship model to simulation-based methods. The outcome of the model could replace conventional training systems and could be useful in effectively transferring surgical skills to novice surgeons.

An efficient soft tissue characterization algorithm from in vivo indentation experiments for medical simulation.

BACKGROUND: Realistic virtual reality surgical training simulators require an accurate biomechanical model of in vivo soft tissue behaviour. One of the challenges in modelling is to characterize soft tissue properties incorporating the experimental measurements of organ behaviour. METHOD: Organ measurements were collected from intra-abdominal organs of pigs, using a robotic indenter and a force transducer. The constitutive model was fitted to the in vivo data using the Levenberg-Marquardt optimization algorithm, combined with a three-dimensional non-linear finite element (FE) simulation. RESULTS: This paper presents an integrated framework for measuring, modelling and calibrating organs' material properties and provides parameters for modelling pigs' intra-abdominal organs. CONCLUSION: The calibrated mechanical models are suitable for computing accurate reaction forces on surgical instruments and for computing the deformations of organs. They also provide a useful benchmark for measuring the realism of real-time tissue models used in virtual reality-based surgical trainers.