Search Results (15)

The prevalence of musculoskeletal symptoms (MSS) like neck and back pain is high among open-surgery surgeons. Prolonged working in the same posture and unfavourable postures are biomechanical risk factors for developing MSS. Ergonomic devices such as exoskeletons are possible solutions that can reduce muscle and joint load. To design effective exoskeletons for surgeons, one needs to quantify which neck and trunk postures are seen and how much support during actual surgery is required. Hence, this study aimed to establish the biomechanical profile of neck and trunk postures and neck and lumbar joint loads during open surgery (training). Eight surgical trainees volunteered to participate in this research. Neck and trunk segment orientations were recorded using an inertial measurement unit (IMU) system during open surgery (training). Neck and lumbar joint kinematics, joint moments and compression forces were computed using OpenSim modelling software and a musculoskeletal model. Histograms were used to illustrate the joint angle and load distribution of the neck and lumbar joints over time. During open surgery, the neck flexion angle was 71.6% of the total duration in the range of 10~40 degrees, and lumbar flexion was 68.9% of the duration in the range of 10~30 degrees. The normalized neck and lumbar flexion moments were 53.8% and 35.5% of the time in the range of 0.04~0.06 Nm/kg and 0.4~0.6 Nm/kg, respectively. Furthermore, the neck and lumbar compression forces were 32.9% and 38.2% of the time in the range of 2.0~2.5 N/kg and 15~20 N/kg, respectively. In contrast to exoskeletons used for heavy lifting tasks, exoskeletons designed for surgeons exhibit lower support torque requirements while additional degrees of freedom (DOF) are needed to accommodate combinations of neck and trunk postures. Full article

Safety plays a key role in human–robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed methodology focuses on the contribution and the mapping of reference frames. Multiple reference frame representation agents are defined at the same time by considering egocentric, allocentric, and route-centric perspectives. The agents are processed to provide a minimal and effective assessment of the ongoing human–robot interactions. The proposed formulation is based on the generalization and proper synthesis of multiple cooperating reference frame agents at the same time. Accordingly, it is possible to achieve a real-time assessment of the safety-related implications through the implementation and fast calculation of proper safety-related quantitative indices. This allows us to define and promptly regulate the controlling parameters of the involved cobot without velocity limitations that are recognized as the main disadvantage. A set of experiments has been realized and investigated to demonstrate the feasibility and effectiveness of the research by using a seven-DOF anthropomorphic arm in combination with a psychometric test. The acquired results agree with the current literature in terms of the kinematic, position, and velocity aspects; use measurement methods based on tests provided to the operator; and introduce novel features of work cell arranging, including the use of virtual instrumentation. Finally, the associated analytical–topological treatments have enabled the development of a safe and comfortable measure to the human–robot relation with satisfactory experimental results compared to previous research. Nevertheless, the robot posture, human perception, and learning technologies would have to apply research from multidisciplinary fields such as psychology, gesture, communication, and social sciences in order to be prepared for positioning in real-world applications that offer new challenges for cobot applications. Full article

For assembly of trans-scale micro-device capsule fill tube assemblies (CFTA) for inertial confinement fusion (ICF) targets, a high-precision space assembly approach based on micro-vision is proposed in this paper. The approach consists of three modules: (i) a posture alignment module based on a multi-vision monitoring model that is designed to align two trans-scale micro-parts in 5DOF while one micro-part is in ten microns and the other one is in hundreds of microns; (ii) an insertion depth control module based on a proposed local deformation detection method to control micro-part insertion depth; (iii) a glue mass control module based on simulation research that is designed to control glue mass quantitatively and to bond micro-parts together. A series of experiments were conducted and experimental results reveal that attitude alignment control error is less than ±0.3°, position alignment control error is less than ±5 µm, and insertion depth control error is less than ±5 μm. Deviation of glue spot diameter is controlled at less than 15 μm. A CFTA was assembled based on the proposed approach, the position error in 3D space measured by computerized tomography (CT) is less than 5 μm, and glue spot diameter at the joint is 56 μm. Through volume calculation by the cone calculation formula, the glue mass is about 23 PL when the cone height is half the diameter. Full article

Six degree-of-freedom (6-DOF) posture measurement is an important academic research topic which has been broadly applied in many fields. As a high-speed photoelectronic sensor with ultra-high resolution and precision, position sensitive detector (PSD) has shown to be one of the most competitive candidates in 6-DOF measurement. This review presents the research progress of PSD-based 6-DOF posture measurement systems in the field of large-scale equipment assembly, ultra-precision manufacturing and other emerging areas. A total of six methods for implementing 6-DOF measurement are summarized and their advantages and limitations are discussed. Meanwhile, the paper illustrates challenges, potential solutions and future development trends. Full article

This paper presents a comparison study of three control design approaches for humanoid balancing based on the Center of Mass ($CoM$) stabilization and body posture adjustment. The comparison was carried out under controlled circumstances allowing other researchers to replicate and compare our results with their own. The feedback control from state space design is based on simple models and provides sufficient robustness to control complex and high Degrees of Freedom (DoFs) systems, such as humanoids. The implemented strategies allow compliant behavior of the robot in reaction to impulsive or periodical disturbances, resulting in a smooth and human-like response while considering constraints. In this respect, we implemented two balancing strategies to compensate for the $CoM$ deviation. The first one uses the robot’s capture point as a stability principle and the second one uses the Force/Torque sensors at the ankles to define a $CoM$ reference that stabilizes the robot. In addition, was implemented a third strategy based on upper body orientation to absorb external disturbances and counterbalance them. Even though the balancing strategies are implemented independently, they can be merged to further increase balancing performance. The proposed strategies were previously applied on different humanoid bipedal platforms, however, their performance could not be properly benchmarked before. With this concern, this paper focuses on benchmarking in controlled scenarios to help the community in comparing different balance techniques. The key performance indicators (KPIs) used in our comparison are the $CoM$ deviation, the settling time, the maximum measured orientation, passive gait measure, measured ankles torques, and reconstructed Center of Pressure ($CoP$). The benchmarking experiments were carried out in simulations and using the facility at Istituto Italiano di Tecnologia on the REEM-C humanoid robot provided by PAL robotics inside the EU H2020 project EUROBENCH framework. Full article

For ultra-precision, large stroke, and high start/stop acceleration, a novel 6-DOF magnetic suspension platform with a novel structure of the permanent array is proposed. The structure and the working principle of the novel platform are introduced. An accurate model of the novel structure was established to calculate the magnetic density distribution for obtaining the parameters and performance of the magnetic suspension platform. The analytical model’s results were verified by the finite element method. The driving force model of the magnetic suspension platform was established based on the Lorentz force. Twelve laser displacement sensors were applied to perceive the posture and vibration acceleration of the platform. The hardware information and the measurement models were introduced and established based on the layout. Finally, the Lorentz force characteristics of the proposed platform were investigated and compared with the conventional magnetic platform by the finite element analysis. The results show that the average magnetic flux density is 0.54T, the horizontal current stiffness along the X-axis is 63.1N/A, the current stiffness along the Y-axis is 61.6N/A, and the average output torque is 7.2 N*cm of the novel platform, larger than those of the conventional ones. Full article

This study aims to quantify wearers’ perceived sensory/tactile comfort responses to clinical and sub-clinical compression socks before, during, and after several activities (postural stability tasks, donning, and doffing). Through purposive sampling, the researchers recruited 20 participants (11 male and 9 female) aged 21.5 ± 2 years. Among all participants, 40% had chronic ankle instability, 30% were copers, and 30% were healthy control groups. Sensory/tactile and movement comfort were assessed using a comfort 8-item questionnaire in a wear trial. The findings exhibit that the tested clinical socks are more comfortable than subclinical socks regardless of the participant types. The strongest positive correlation was between material appearance and hand feel (r = 0.84, ** p < 0.01) and between ‘no red marks’ and non-itchiness (r = 0.72, ** p < 0.01). Additionally, no statistically significant differences in comparisons of comfort assessment measures were reported. However, due to the consistency of the trends in differences, the researchers suggest that these findings warrant additional research using a more robust sampling technique. According to the findings of this study, a higher-pressure level compression sock may be preferable for patients with ankle stability issues, as there is no significant evidence for a comforting outcome. Full article

Thanks to the rapid development of Wearable Fitness Trackers (WFTs) and Smartphone Pedometer Apps (SPAs), people are keeping an eye on their health through fitness and heart rate tracking; therefore, home weight training exercises have received a lot of attention lately. A multi-procedure intelligent algorithm for weight training using two inertial measurement units (IMUs) is proposed in this paper. The first procedure is for motion tracking that estimates the arm orientation and calculates the positions of the wrist and elbow. The second procedure is for posture recognition based on deep learning, which identifies the type of exercise posture. The final procedure is for exercise prescription variables, which first infers the user’s exercise state based on the results of the previous two procedures, triggers the corresponding event, and calculates the key indicators of the weight training exercise (exercise prescription variables), including exercise items, repetitions, sets, training capacity, workout capacity, training period, explosive power, etc.). This study integrates the hardware and software as a complete system. The developed smartphone App is able to receive heart rate data, to analyze the user’s exercise state, and to calculate the exercise prescription variables automatically in real-time. The dashboard in the user interface of the smartphone App can display exercise information through Unity’s Animation System (avatar) and graphics, and records are stored by the SQLite database. The designed system was proven by two types of experimental verification tests. The first type is to control a stepper motor to rotate the designed IMU and to compare the rotation angle obtained from the IMU with the rotation angle of the controlled stepper motor. The average mean absolute error of estimation for 31 repeated experiments is 1.485 degrees. The second type is to use Mediapipe Pose to calculate the position of the wrist and the angles of upper arm and forearm between the Z-axis, and these calculated data are compared with the designed system. The root-mean-square (RMS) error of positions of the wrist is 2.43 cm, and the RMS errors of two angles are 5.654 and 4.385 degrees for upper arm and forearm, respectively. For posture recognition, 12 participants were divided into training group and test group. Eighty percent and 20% of 24,963 samples of 10 participants were used for the training and validation of the LSTM model, respectively. Three-thousand-three-hundred-and-fifty-nine samples of two participants were used to evaluate the performance of the trained LSTM model. The accuracy reached 99%, and F1 score was 0.99. When compared with the other LSTM-based variants, the accuracy of one-layer LSTM presented in this paper is still promising. The exercise prescription variables provided by the presented system are helpful for weight trainers/trainees to closely keep an eye on their fitness progress and for improving their health. Full article

For large bearing capacity and low current consumption of the magnetic suspension platform, a 2-DOF electromagnetic actuator with a new structure of halbach array is proposed to improve driving force coefficients. The structure and the working principle are introduced. An accurate sub domain model of the new structure is established to accurately and rapidly calculate the magnetic field distribution for obtaining the parameters and performance of the electromagnetic actuators. The analytical model results are verified by the finite element method. The force/torque model of the magnetic suspension platform is established based on the proposed 2-DOF electromagnetic actuator. Three position-sensitive detectors and six accelerometers are applied to perceive in real time the posture and vibration acceleration of the platform, respectively. Their hardware information is introduced and measurement models are established based on the layout. Finally, the electromagnetic characteristics of the proposed actuator are investigated and compared with the conventional counterpart by finite element analysis. The results show that the average magnetic field, 0.432 T, horizontal and vertical force coefficient, 92.3 N/A and 30.95 N/A, and torque in x and z direction, 3.61 N·m and 8.49 N·m, of the proposed actuator are larger than those of the conventional one. Full article

In rehabilitation, assistive and space robotics, the capability to track the body posture of a user in real time is highly desirable. In more specific cases, such as teleoperated extra-vehicular activity, prosthetics and home service robotics, the ideal posture-tracking device must also be wearable, light and low-power, while still enforcing the best possible accuracy. Additionally, the device must be targeted at effective human-machine interaction. In this paper, we present and test such a device based upon commercial inertial measurement units: it weighs 575 g in total, lasts up to 10.5 h of continual operation, can be donned and doffed in under a minute and costs less than 290 EUR. We assess the attainable performance in terms of error in an online trajectory-tracking task in Virtual Reality using the device through an experiment involving 10 subjects, showing that an average user can attain a precision of 0.66 cm during a static precision task and 6.33 cm while tracking a moving trajectory, when tested in the full peri-personal space of a user. Full article

This paper presents a fingertip grip force sensor based on custom capacitive sensors for glove-type assistive devices with an open-pad structure. The design of the sensor allows using human tactile sensations during grasping and manipulating an object. The proposed sensor can be attached on both sides of the fingertip and measure the force caused by the expansion of the fingertip tissue when a grasping force is applied to the fingertip. The number of measurable degrees of freedom (DoFs) are the two DoFs (flexion and adduction) for the thumb and one DoF (flexion) for the index and middle fingers. The proposed sensor allows the combination with a glove-type assistive device to measure the fingertip force. Calibration was performed for each finger joint angle because the variations in the expansion of the fingertip tissue depend on the joint angles. The root mean square error (RMSE) for fingertip force estimation ranged from 3.75% to 9.71% after calibration, regardless of the finger joint angles or finger posture. Full article

With the increasing demand for robots to react and adapt to unforeseen events, it is essential that a robot preserves agility at all times. While manipulability is a common measure to quantify agility at a given joint configuration, an efficient direct evaluation in task space is usually not possible with conventional methods, especially for redundant robots with an infinite number of Inverse Kinematic solutions. Yet, this is essential for global online optimization of a robot posture. In this work, we derive analytical expressions for a conventional 7-degrees of freedom (7-DOF) serial robot structure, which enable the direct evaluation of manipulability from a reduced task space parametrization. The resulting expressions allow array operation and thus achieve very high computational efficiency with vector-optimized programming languages. This direct and simultaneous calculation of the task space manipulability for large numbers of poses benefits many optimization problems in robotic applications. We show applications in global optimization of robot mounting poses, as well as redundancy resolution with global online optimization w.r.t. manipulability. Full article

We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation. Full article

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. Full article

We present a new calibration procedure for low-cost nine degrees-of-freedom (9DOF) magnetic, angular rate and gravity (MARG) sensor systems, which relies on a calibration cube, a reference table and a body sensor network (BSN). The 9DOF MARG sensor is part of our recently-developed “Integrated Posture and Activity Network by Medit Aachen” (IPANEMA) BSN. The advantage of this new approach is the use of the calibration cube, which allows for easy integration of two sensor nodes of the IPANEMA BSN. One 9DOF MARG sensor node is thereby used for calibration; the second 9DOF MARG sensor node is used for reference measurements. A novel algorithm uses these measurements to further improve the performance of the calibration procedure by processing arbitrarily-executed motions. In addition, the calibration routine can be used in an alignment procedure to minimize errors in the orientation between the 9DOF MARG sensor system and a motion capture inertial reference system. A two-stage experimental study is conducted to underline the performance of our calibration procedure. In both stages of the proposed calibration procedure, the BSN data, as well as reference tracking data are recorded. In the first stage, the mean values of all sensor outputs are determined as the absolute measurement offset to minimize integration errors in the derived movement model of the corresponding body segment. The second stage deals with the dynamic characteristics of the measurement system where the dynamic deviation of the sensor output compared to a reference system is Sensors 2015, 15 25920 corrected. In practical validation experiments, this procedure showed promising results with a maximum RMS error of 3.89°. Full article