RESUMO
BACKGROUND: Pathological gaits of children may lead to terrible diseases, such as osteoarthritis or scoliosis. By monitoring the gait pattern of a child, proper therapeutic measures can be recommended to avoid the terrible consequence. However, low-cost systems for pathological gait recognition of children automatically have not been on market yet. Our goal was to design a low-cost gait-recognition system for children with only pressure information. METHODS: In this study, we design a pathological gait-recognition system (PGRS) with an 8 × 8 pressure-sensor array. An intelligent gait-recognition method (IGRM) based on machine learning and pure plantar pressure information is also proposed in static and dynamic sections to realize high accuracy and good real-time performance. To verifying the recognition effect, a total of 17 children were recruited in the experiments wearing PGRS to recognize three pathological gaits (toe-in, toe-out, and flat) and normal gait. Children are asked to walk naturally on level ground in the dynamic section or stand naturally and comfortably in the static section. The evaluation of the performance of recognition results included stratified tenfold cross-validation with recall, precision, and a time cost as metrics. RESULTS: The experimental results show that all of the IGRMs have been identified with a practically applicable degree of average accuracy either in the dynamic or static section. Experimental results indicate that the IGRM has 92.41% and 97.79% intra-subject recognition accuracy, and 85.78% and 78.81% inter-subject recognition accuracy, respectively, in the static and dynamic sections. And we find methods in the static section have less recognition accuracy due to the unnatural gesture of children when standing. CONCLUSIONS: In this study, a low-cost PGRS has been verified and realize feasibility, highly average precision, and good real-time performance of gait recognition. The experimental results reveal the potential for the computer supervision of non-pathological and pathological gaits in the plantar-pressure patterns of children and for providing feedback in the application of gait-abnormality rectification.
Assuntos
Marcha , Caminhada , Criança , Retroalimentação , Humanos , Aprendizado de MáquinaRESUMO
Docking technology for autonomous underwater vehicles (AUVs) involves energy supply, data exchange and navigation, and plays an important role to extend the endurance of the AUVs. The navigation method used in the transition between AUV homing and docking influences subsequent tasks. How to improve the accuracy of the navigation in this stage is important. However, when using ultra-short baseline (USBL), outliers and slow localization updating rates could possibly cause localization errors. Optical navigation methods using underwater lights and cameras are easily affected by the ambient light. All these may reduce the rate of successful docking. In this paper, research on an improved localization method based on multi-sensor information fusion is carried out. To improve the localization performance of AUVs under motion mutation and light variation conditions, an improved underwater simultaneous localization and mapping algorithm based on ORB features (IU-ORBSALM) is proposed. A nonlinear optimization method is proposed to optimize the scale of monocular visual odometry in IU-ORBSLAM and the AUV pose. Localization tests and five docking missions are executed in a swimming pool. The localization results indicate that the localization accuracy and update rate are both improved. The 100% successful docking rate achieved verifies the feasibility of the proposed localization method.
RESUMO
With the help of wearable robotics, the lower limb exoskeleton becomes a promising solution for spinal cord injury (SCI) patients to recover lower body locomotion ability. However, fewer exoskeleton gait planning methods can meet the needs of patient in real time, e.g., stride length or step width, etc., which may lead to human-machine incoordination, limit comfort, and increase the risk of falling. This work presents a human-exoskeleton-crutch system with the center of pressure (CoP)-based gait planning method to enable the balance control during the exoskeleton-assisted walking with crutches. The CoP generated by crutches and human-machine feet makes it possible to obtain the overall stability conditions of the system in the process of exoskeleton-assisted quasi-static walking, and therefore, to determine the next stride length and ensure the balance of the next step. Thus, the exoskeleton gait is planned with the guidance of stride length. It is worth emphasizing that the nominal reference gait is adopted as a reference to ensure that the trajectory of the swing ankle mimics the reference one well. This gait planning method enables the patient to adaptively interact with the exoskeleton gait. The online gait planning walking tests with five healthy volunteers proved the method's feasibility. Experimental results indicate that the algorithm can deal with the sensed signals and plan the landing point of the swing leg to ensure balanced and smooth walking. The results suggest that the method is an effective means to improve human-machine interaction. Additionally, it is meaningful for the further training of independent walking stability control in exoskeletons for SCI patients with less assistance of crutches.
Assuntos
Muletas , Exoesqueleto Energizado , Análise da Marcha , Extremidade Inferior , Caminhada , Humanos , Traumatismos da Medula Espinal/reabilitaçãoRESUMO
Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations.
RESUMO
This study presents a device for tracking, locating and communicating underwater vehicles as they work near the seabed. The system includes a base station placed on the seabed and a reflective module mounted on a hybrid underwater profiler (HUP). The base station localizes and communicates with the HUP working near the seabed based on laser reflections of corner cube retroreflectors. A tracking method based on the particle filter algorithm is then presented. Localization is performed using the least-squares method with refraction compensation. Lost tracking links are retrieved via a recovering approach based on the interpolation method. Finally, a communication method using a modulating retroreflector installed on the reflection module is proposed. The proposed tracking, localization, and communication approach provides higher localization accuracy with lower power consumption at low cost compared with the commonly used acoustic methods. The effectiveness of the proposed approach was clarified via tracking, localization, and communication experiments.
RESUMO
Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.
Assuntos
Algoritmos , Exoesqueleto Energizado , Monitorização Ambulatorial/métodos , Reabilitação , Aceleração , Humanos , Robótica , Caminhada/fisiologiaRESUMO
Long-term in situ measurements of the temperature of hydrothermal fluids have great significance in the research of seafloor hydrothermal activities. Herein, we developed a self-powered battery-free temperature logger for measuring and recording the temperature of hydrothermal fluids. A gravity heat pipe made of titanium alloy was employed as the heat-conducting element of the temperature logger to capture heat from a hydrothermal vent and transfer it to the thermoelectric unit. The thermoelectric generator used herein converted the temperature difference into electrical energy to power the circuit of the temperature logger. Numerical analyses and experiments were performed to investigate the performance of the heat pipe and temperature logger. Results show that the temperature logger can realize self-powered starting at a temperature of >76 °C during a tank test. This paper presents a discussion on a new instrument for temperature measurements of deep-sea hydrothermal fluids.
RESUMO
Introduction: Human-in-the-loop optimization has made great progress to improve the performance of wearable robotic devices and become an effective customized assistance strategy. However, a lengthy period (several hours) of continuous walking for iterative optimization for each individual makes it less practical, especially for disabled people, who may not endure this process. Methods: In this paper, we provide a muscle-activity-based human-in-the-loop optimization strategy that can reduce the time spent on collecting biosignals during each iteration from around 120 s to 25 s. Both Bayesian and Covariance Matrix Adaptive Evolution Strategy (CMA-ES) optimization algorithms were adopted on a portable hip exoskeleton to generate optimal assist torque patterns, optimizing rectus femoris muscle activity. Four volunteers were recruited for exoskeleton-assisted walking trials. Results and Discussion: As a result, using human-in-the-loop optimization led to muscle activity reduction of 33.56% and 41.81% at most when compared to walking without and with the hip exoskeleton, respectively. Furthermore, the results of human-in-the-loop optimization indicate that three out of four participants achieved superior outcomes compared to the predefined assistance patterns. Interestingly, during the optimization stage, the order of the two typical optimizers, i.e., Bayesian and CMA-ES, did not affect the optimization results. The results of the experiment have confirmed that the assistance pattern generated by muscle-activity-based human-in-the-loop strategy is superior to predefined assistance patterns, and this strategy can be achieved more rapidly than the one based on metabolic cost.
RESUMO
The aging population is now a global challenge, and impaired walking ability is a common feature in the elderly. In addition, some occupations such as military and relief workers require extra physical help to perform tasks efficiently. Robotic hip exoskeletons can support ambulatory functions in the elderly and augment human performance in healthy people during normal walking and loaded walking by providing assistive torque. In this review, the current development of robotic hip exoskeletons is presented. In addition, the framework of actuation joints and the high-level control strategy (including the sensors and data collection, the way to recognize gait phase, the algorithms to generate the assist torque) are described. The exoskeleton prototypes proposed by researchers in recent years are organized to benefit the related fields realizing the limitations of the available robotic hip exoskeletons, therefore, this work tends to be an influential factor with a better understanding of the development and state-of-the-art technology.
RESUMO
In recent years, a huge number of individuals all over the world, elderly people, in particular, have been suffering from Alzheimer's disease (AD), which has had a significant negative impact on their quality of life. To intervene early in the progression of the disease, accurate, convenient, and low-cost detection technologies are gaining increased attention. As a result of their multiple merits in the detection and assessment of AD, biosensors are being frequently utilized in this field. Behavioral detection is a prospective way to diagnose AD at an early stage, which is a more objective and quantitative approach than conventional neuropsychological scales. Furthermore, it provides a safer and more comfortable environment than those invasive methods (such as blood and cerebrospinal fluid tests) and is more economical than neuroimaging tests. Behavior detection is gaining increasing attention in AD diagnosis. In this review, cutting-edge biosensor-based devices for AD diagnosis together with their measurement parameters and diagnostic effectiveness have been discussed in four application subtopics: body movement behavior detection, eye movement behavior detection, speech behavior detection, and multi-behavior detection. Finally, the characteristics of behavior detection sensors in various application scenarios are summarized and the prospects of their application in AD diagnostics are presented as well.
RESUMO
Nowadays, wearable devices mainly exist in the form of portable accessories with various functions, connecting various kinds of terminals like mobile phones to form various wearable systems. In a wearable system, the wearable power supply device is the key component as energy dispenser for all devices. Nanosheets, a kind of two-dimensional material, which always displays a high surface-to-volume ratio and thus is lightweight and has remarkable conductive as well as electrochemical properties, have become the optimal choice for wearable power supply devices. The development and status of nanosheet-based wearable power supply devices including nanosheet-based wearable batteries, nanosheet-based wearable supercapacitors, nanosheet-based wearable self-powered energy suppliers are introduced in this article. Besides, the future opportunities and challenges of wearable devices are discussed.
RESUMO
This paper presents a novel isobaric sample transfer apparatus developed to facilitate the continuous culture of microorganisms while also providing the capacity for maintaining the sample at in situ pressure during the whole transfer and culture process. This apparatus is fitted to the isobaric fluid sampler which is used for collecting the isobaric fluid sample. This apparatus can not only avoid decompression in traditional sample transfer but also realize the integrated function of sample transfer and culture under isobaric conditions. The subsampling cylinder can automatically work as a flow culture reactor after completing the subsampling of the pressurized sample. Several transfer experiments were carried out to demonstrate this design which can make the period of transfer automatically.
RESUMO
This paper describes the design of a flexible titanium foil cell, as well as its applications in hydrothermal experiments and in non-contaminating storage of seafloor hydrothermal fluids. A flexible cell constructed totally from pure titanium (Grade 1) can be used in corrosive environment because of the excellent chemical stability and temperature tolerance of the material. Theoretical calculation and finite element analysis of the titanium foil cell have been conducted to identify its flexibility and deformation mode. Two applications, i.e., hydrothermal reaction and non-contaminating fluid sampling, were introduced subsequently. The flexible titanium foil cell was successfully tested at elevated temperature and pressure of up to 400 °C and 40 MPa, respectively, demonstrating that it could be widely used under supercritical water conditions.
RESUMO
A new hybrid event based control architecture for tele-robotic systems controlled through the Internet is proposed in this paper. Different from the traditional event based control method, the new framework does not require every part of the system to be strictly event synchronized. Instead, it allows time referenced control components to be integrated into this framework, which makes it more convenient to develop Internet based control systems. Since there are two reference variables, time and event, in this architecture, how to coordinate these components with different references to keep the stability of the whole system is discussed in detail in this paper. To verify this new idea, an experiment was conducted to control the end effector of a PUMA robot tracking a continuous state trajectory given on-line by the remote operator. Experimental results confirmed the stability of such systems being controlled through the Internet in real-time.