Assessment of hand kinematics is important when evaluating hand functioning. Major drawbacks of current sensing glove systems are lack of rotational observability in particular directions, labour intensive calibration methods which are sensitive to wear and lack of an absolute hand orientation estimate.

In this paper, we present the design, control, and preliminary evaluation of the Symbitron exoskeleton, a lower limb modular exoskeleton developed for people with a spinal cord injury. The mechanical and electrical configuration and the controller can be personalized to accommodate differences in impairments among individuals with spinal cord injuries (SCI). In hardware, this personalization is accomplished by a modular approach that allows the reconfiguration of a lower-limb exoskeleton with ultimately eight powered series actuated (SEA) joints and high fidelity torque control. For SCI individuals with an incomplete lesion and sufficient hip control, we applied a trajectory-free neuromuscular control (NMC) strategy and used the exoskeleton in the ankle-knee configuration. For complete SCI individuals, we used a combination of a NMC and an impedance based trajectory tracking strategy with the exoskeleton in the ankle-knee-hip configuration. Results of a preliminary evaluation of the developed hardware and software showed that SCI individuals with an incomplete lesion could naturally vary their walking speed and step length and walked faster compared to walking without the device. SCI individuals with a complete lesion, who could not walk without support, were able to walk with the device and with the support of crutches that included a push-button for step initiation Our results demonstrate that an exoskeleton with modular hardware and control allows SCI individuals with limited or no lower limb function to receive tailored support and regain mobility.

The currently accepted interval of weekly cast changes in the treatment of clubfeet seems unsubstantiated. A force sensor is needed to determine the adaptation rate of a clubfoot to establish what cast change interval would be most effective and efficient. We developed a force sensor based on the principle that the resonance frequency of an LC-tank changes when a metal target is brought in close proximity. A thin rubber ring between the LC-tank and the metal target transformed this proximity sensor into a force sensor. With a static load test and an incremental load test, the performance of the constructed force sensors was characterized. The custom-made sensor showed excellent sensitivity (($1.7\pm 0.8\times {10}^5$) counts/N), resolution (($0.15\pm 0.06$) mN), and accuracy (($3.5\pm 3.0$) %) for the application. The observed drift was ($2.1\pm 0.7$) %/log${}_{10}$(h), which is lower than other thin force sensors. Preliminary results of measurements in the treatment of Dupuytren fingers and clubfeet show good functioning for long-term force measurements.

Operating in extreme environments is often challenging due to the lack of perceptual knowledge. During fire incidents in large buildings, the extreme levels of smoke can seriously impede a firefighter’s vision, potentially leading to severe material damage and loss of life. To increase the safety of firefighters, research is conducted in collaboration with Dutch fire departments into the usability of Unmanned Ground Vehicles to increase situational awareness in hazardous environments. This paper proposes FirebotSLAM, the first algorithm capable of coherently computing a robot’s odometry while creating a comprehensible 3D map solely using the information extracted from thermal images. The literature showed that the most challenging aspect of thermal Simultaneous Localization and Mapping (SLAM) is the extraction of robust features in thermal images. Therefore, a practical benchmark of feature extraction and description methods was performed on datasets recorded during a fire incident. The best-performing combination of extractor and descriptor is then implemented into a state-of-the-art visual SLAM algorithm. As a result, FirebotSLAM is the first thermal odometry algorithm able to perform global trajectory optimization by detecting loop closures. Finally, FirebotSLAM is the first thermal SLAM algorithm to be tested in a fiery environment to validate its applicability in an operational scenario.

The purpose of this study is to investigate the technical feasibility of measuring relative positions and orientations of the tibia with respect to the femur in an in-vitro experiment by using a 3D-tracked A-mode ultrasound system and to determine its accuracy of angular and translational measurements. As A-mode ultrasound is capable of detecting bone surface through soft tissue in a non-invasive manner, the combination of a single A-mode ultrasound transducer with an optical motion tracking system provides the possibility for digitizing the 3D locations of bony points at different anatomical regions on the thigh and the shank. After measuring bony points over a large area of both the femur and tibia, the bone models of the femur and tibia that were segmented from CT or MRI images were registered to the corresponding bony points. Then the relative position of the tibia with respect to the femur could be obtained and the angular and translational components could also be measured. A cadaveric experiment was conducted to assess its accuracy compared to the reference measurement obtained by optical markers fixed to intra-cortical bone pins placed in the femur and tibia. The results showed that the ultrasound system could achieve 0.49 ± 0.83°, 0.85 ± 1.86° and 1.85 ± 2.78° (mean ± standard deviation) errors for Flexion-Extension, Adduction-Abduction and External-Internal rotations, respectively, and -2.22 ± 3.62 mm, -2.80 ± 2.35 mm and -1.44 ± 2.90 mm errors for Anterior-Posterior, Proximal-Distal and Lateral-Medial translations, respectively. It was concluded that this technique is feasible and facilitates the integration of arrays of A-mode ultrasound transducers with an optical motion tracking system for non-invasive dynamic tibiofemoral kinematics measurement.

This paper introduces a method for measuring 3D tibiofemoral kinematics using a multi-channel A-mode ultrasound system under dynamic conditions. The proposed system consists of a multi-channel A-mode ultrasound system integrated with a conventional motion capture system (i.e., optical tracking system). This approach allows for the non-invasive and non-radiative quantification of the tibiofemoral joint’s six degrees of freedom (DOF). We demonstrated the feasibility and accuracy of this method in the cadaveric experiment. The knee joint’s motions were mimicked by manually manipulating the leg through multiple motion cycles from flexion to extension. To measure it, six custom ultrasound holders, equipped with a total of 30 A-mode ultrasound transducers and 18 optical markers, were mounted on various anatomical regions of the lower extremity of the specimen. During experiments, 3D-tracked intra-cortical bone pins were inserted into the femur and tibia to measure the ground truth of tibiofemoral kinematics. The results were compared with the tibiofemoral kinematics derived from the proposed ultrasound system. The results showed an average rotational error of 1.51 ± 1.13° and a translational error of 3.14 ± 1.72 mm for the ultrasound-derived kinematics, compared to the ground truth. In conclusion, this multi-channel A-mode ultrasound system demonstrated a great potential of effectively measuring tibiofemoral kinematics during dynamic motions. Its improved accuracy, nature of non-invasiveness, and lack of radiation exposure make this method a promising alternative to incorporate into gait analysis and prosthetic kinematic measurements later.