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An intelligent walking-aid cane robot is developed for assisting the elderly and the physically challenged with walking. A motion control method is proposed for the cane robot based on human walking intention estimation. Moreover, the safety is investigated for both the cane robot and the elderly. The fall detection and prevention concepts are prop...
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... of the cane robot to prevent the user from falling is to bend its stick in the opposite direction of the thrust F 1 [14]. This causes the dynamic motions of the falling user and the cane robot to occur in the same plane. Thus, the fall prevention control can be described by a two-dimensional dynamic model, as shown in Fig. 9. As illustrated in Fig. 10, the user is modeled as a two- dimensional inverted pendulum, and the cane robot is regarded as a planar mobile manipulator with one link. The contact point between the user and the cane robot is denoted by P . During the fall prevention procedure, we assume that the user will maintain the distance between point P and the user's body. ...
Citations
... Cane Walking Assistants (CWA) are like a walking stick and their relatively small size makes them easy to use both indoors and outdoors. Although small, the CWA provides the necessary stability for people who are confident enough in their gait to require little or no assistance [152]. ...
... The authors, Di et al. 2016, propose an intelligent cane robot that includes an omnidirectional base, a universal joint that connects the cane to the base, a laser rangefinder (LRF) sensor, a forcetorque (FT) sensor, and a touch panel. They also propose a fall detection and prevention system that uses a load sensor in the insole that users wear inside their shoes. ...
... They also propose a fall detection and prevention system that uses a load sensor in the insole that users wear inside their shoes. The combination of load sensor data, LRF and FT sensor data, acoustic sensors, Charge Coupled Device (CCD), localization cameras and RGB depth cameras can enable the robot to perform these activities and provide an impedancebased fall prevention controller [131,152]. ...
Robotic systems are increasingly being used in healthcare to improve patient care and support healthcare professionals. These robots are especially effective at performing repetitive tasks. In complex cancer cases, robots can enhance surgical precision and efficiency, resulting in reduced pain for patients and a lower risk of complications. Robot-assisted surgery offers high-quality 3D imaging, improved clarity, and increased efficiency. This review paper examines the application of Artificial Intelligence (AI) and robotic systems in the healthcare domain, specifically focusing on the interaction among operators, patients, and robots. The goal is to promote collaboration and improve healthcare provision through human-robot interaction. We considered already published articles by relevance, to identify the primary safety issues that need addressing for the integration of AI and robots in hospitals. Concluding with insights into understanding the focal points of social errors in Human-Robot Interaction (HRI) is crucial for mitigating these errors. While current technologies have reached a certain level of maturity, there are still numerous challenges in utilizing robot-assisted clinical practice, including technological, safety, clinical, financial, insurance, psychological, social, ethical, and legal issues. In addition, there is an urgent issue that needs to be addressed: the alignment of values in artificial intelligence, ensuring that AI systems reflect ethical principles and human values is crucial to avoid negative consequences such as bias, discrimination, and prejudicial decisions. Resolving this complex issue requires collaboration among clinical staff, researchers, programmers, and political decision-makers from various fields.
... In recent years, the development of robotic systems has been increasingly focused on assisting individuals in various daily activities [4][5][6][7] , notably in mobility assistance [8][9][10][11][12][13][14][15][16][17][18][19][20][21] . Walking-aid robots have emerged as important tools, assisting individuals with limited mobility to walk in various terrains. ...
This paper introduces an innovative staircase shape feature extraction method for walking-aid robots to enhance environmental perception and navigation. We present a robust method for accurate feature extraction of staircases under various conditions, including restricted viewpoints and dynamic movement. Utilizing depth camera-mounted robots, we transform three-dimensional (3D) environmental point cloud into two-dimensional (2D) representations, focusing on identifying both convex and concave corners. Our approach integrates the Random Sample Consensus algorithm with K-Nearest Neighbors (KNN)-augmented Iterative Closest Point (ICP) for efficient point cloud registration. The results show an improvement in trajectory accuracy, with errors within the centimeter range. This work overcomes the limitations of previous approaches and is of great significance for improving the navigation and safety of walking assistive robots, providing new possibilities for enhancing the autonomy and mobility of individuals with physical disabilities.
... We argue that intelligence is essential for a robotic walker to protect the safety of the patients, since primitive assistance devices, such as rollators and walkers, are much more likely to fail [2] . Present-day assistant devices require attentive control of the user while moving [3,4] , which could raise safety issues for many patients with insufficient upper body strength and cause bad coordination between the human-exoskeleton system and the robotic walker. A few studies have investigated the task enabling the walker to follow behind the user by detecting his/her trajectory beforehand [5] . ...
Overground walking can be achieved for patients with gait impairments by using the lower limb exoskeleton robots. Since it is a challenge to keep balance for patients with insufficient upper body strength, a robotic walker is necessary to assist with the walking balance. However, since the walking pattern varies over time, controlling the robotic walker to follow the walking of the human-exoskeleton system in coordination is a critical issue. Inappropriate control strategy leads to the unnecessary energy cost of the human-exoskeleton-walker (HEW) system and also results in the bad coordination between the human-exoskeleton system and the robotic walker. In this paper, we proposed a Coordinated Energy-Efficient Control (CEEC) approach for the HEW system, which is based on the extremum seeking control algorithm and the coordinated motion planning strategy. First, the extremum seeking control algorithm is used to find the optimal supporting force of the support joint in real time to maximize the energy efficiency of the human-exoskeleton system. Second, the appropriate reference joint angles for wheels of the robotic walker can be generated by the coordinated motion planning strategy, causing the good coordination between the human-exoskeleton system and the robotic walker. The proposed approach has been tested on the HEW simulation model, and the experimental results indicate that the coordinated energy-efficient walking can be achieved with the proposed approach, which is increased by 60.16% compared to the conventional passive robotic walker.
... Cane-type assistive robots, like the one in [6], allow single-handed use. For instance, the tool in [7] employs force/torque and distance measurements for robot positioning, fall detection, and balance restoration. However, these platforms primarily rely on upperbody functions for support and safety, limiting accessibility to a narrower range of users. ...
... In [10], a force/torque sensor was attached to the handle of a canetype robot, and the measured force was employed to generate the robot's desired velocity. This approach also addresses fall prevention and balance by considering the user's center of pressure (COP) [7]. Human motion detection plays a crucial role in enhancing walking assistance capability, particularly for safety measures such as fall prevention and detecting mismatches in human-robot movement that could lead to unsafe situations. ...
... Building upon human skeletal movement, including the upper body, we aim to enhance assistive performance securely, with a focus on fall prevention. In a previous study [7], instances of falling were identified by monitoring the COP using a cane-type robot, which maintained the COP within a support triangle defined by the feet and robot positions. With access to skeletal data from both the upper and lower body, we can detect unbalanced postures and potential falls earlier. ...
Walking aid robots have been developed for elderly people or patients facing difficulties while walking. However, most of them are designed only for flat ground, must rely on handles, and have drawbacks such as oscillation and lack of stability. The primary goal of this research is to improve the transparency and safety of a walking aid robot, addressing both flat and sloping terrains. To achieve this goal, we propose a novel variable admittance control strategy for an omnidirectional mobile platform by combining human motion recognition and a slope-adaptive approach. We design a vision system with a wide-angle camera to capture skeletal whole-body information at a close distance to recognize the walking direction. Accordingly, the damping values of the admittance controller are varied. In addition, these parameters are varied with respect to the slope angle of the ground, which is detected by the platform. We validated the controller performance with eleven healthy subjects performing two experiments on both flat and sloping terrains. Three admittance controllers are compared, with fixed parameters, variable damping by Cartesian velocity, and variable damping by walking direction. Experimental results show the advantages of the variable admittance control based on walking direction, which ensures high transparency and smoothness on both flat and sloping terrains.
... Existing methods can be summarized as conventional machine learning and deep learning [6]. Through constructing manual bipedal or weak foot features, simple classifiers can output results at the cost of scalability [44], [45]. Dispense with feature engineering, deep learning methods could also output results in real-time by fewer raw gaits. ...
In cross-subject fall risk classification based on plantar pressure, a challenge is that data from different subjects have significant individual information. Thus, the models with insufficient generalization ability can’t perform well on new subjects, which limits their application in daily life. To solve this problem, domain adaptation methods are applied to reduce the gap between source and target domain. However, these methods focus on the distribution of the source and the target domain, but ignore the potential correlation among multiple source subjects, which deteriorates domain adaptation performance. In this paper, we proposed a novel method named domain adaptation with subject fusion (SFDA) for fall risk assessment, greatly improving the cross-subject assessment ability. Specifically, SFDA synchronously carries out source target adaptation and multiple source subject fusion by domain adversarial module to reduce source-target gap and distribution distance within source subjects of same class. Consequently, target samples can learn more task-specific features from source subjects to improve the generalization ability. Experiment results show that SFDA achieved mean accuracy of 79.17 % and 73.66 % based on two backbones in a cross-subject classification manner, outperforming the state-of-the-art methods on continuous plantar pressure dataset. This study proves the effectiveness of SFDA and provides a novel tool for implementing cross-subject and few-gait fall risk assessment.
... The study in [44] demonstrates the experimental results of fall detection and prevention using a cane robot. Non-disabled male participants walked with the cane robot, and their "normal walking" and "abnormal walking" data were recorded. ...
An accurate, economical, and reliable device for detecting falls in persons ambulating with the assistance of an orthopedic walker is crucially important for the elderly and patients with limited mobility. Existing wearable devices, such as wristbands, are not designed for walker users, and patients may not wear them at all times. This research proposes a novel idea of attaching an internet-of-things (IoT) device with an inertial measurement unit (IMU) sensor directly to an orthopedic walker to perform real-time fall detection and activity logging. A dataset is collected and labeled for walker users in four activities, including idle, motion, step, and fall. Classic machine learning algorithms are evaluated using the dataset by comparing their classification performance. Deep learning with a convolutional neural network (CNN) is also explored. Furthermore, the hardware prototype is designed by integrating a low-power microcontroller for onboard machine learning, an IMU sensor, a rechargeable battery, and Bluetooth wireless connectivity. The research results show the promise of improved safety and well-being of walker users.
... Several researchers have investigated the use of lower-limb exoskeletal devices to facilitate balance, which could potentially preclude the initiation of falls (e.g., Vallery et al., 2012;Tucker et al., 2015;Ugurlu et al., 2015;Wang et al., 2015;Yan et al., 2015;Di et al., 2016;Huynh et al., 2018;Zhang et al., 2018;Fasola et al., 2019;Hamza et al., 2020). Employing a lower limb exoskeleton to arrest the onset of an initiated fall, however, has not yet been studied. ...
This article examines the feasibility of employing a cold-gas thruster (CGT), intended as a backpack-wearable device, for purposes of arresting backward falls, and in particular describes a supervisory controller that, for some motion described by an arbitrary combination of center-of-mass angle and angular velocity, both detects an impending fall and determines when to initiate thrust in the CGT in order to arrest the impending fall. The CGT prototype and the supervisory controller are described and experimentally assessed using a rocking block apparatus intended to approximate a backward-falling human. In these experiments, the CGT and supervisory controller restored upright stability to the rocking block in all experiment cases that would have otherwise resulted in a fall without the CGT assistance. Since the controller and experiments employ a reduced-order model of a falling human, the authors also conducted a series of simulations intended to examine the extent to which the controller might remain effective in the case of a multi-segment human. The results of these simulations suggest that the CGT controller would be nearly as effective on a multi-segment falling human as on the reduced-order model.
... Therefore, the recent years has seen an increase in the use of lift-type robots, which lift only the upper body [1], [2]. For walking support, wearable [5], walker-type [6], [7, [8], and cane-type [9], [10] robots have been developed. The wearable system in [5] is a walking support system that utilizes the residual muscle strength of the elderly person with the minimum force necessary, making good use of spring force when the legs are extended. ...
... The walker type robot in [13] measures the user's gait by using Laser Range Finders (LRFs). The cane robot in [10], [14], and [32] can estimate the user's falling by using information about the user's legs and force information which can be measured by using LRFs and the force sensors on the handles. It can then prevent the user from falling by stopping itself. ...
The importance of care robots is growing owing to the increasing numbers of the elderly and the shortage of caregivers. For robots to automatically assist the movements of the elderly users, the state of their pose should be estimated. Hence, we proposed a method for estimating the user’s state using candidate positions of the center of gravity of the robot user using a few sensors. In this method, sensor outputs in all states and movements of the user are collected in advance, and a state estimation and abnormality detection model created by machine learning using the relationship between the outputs and state is used as training data. However, it is difficult to collect training data pertaining to elderly people, before use, for this purpose. Therefore, a database of human actions is created for use as the training data. Rich databases of such actions performed sans robots already exist, but not where care robots are used. Conventional methods for simulating human body movements to estimate human states require actual data and expert coordination and do not address detailed state estimation for physical support. Therefore, this study proposed a method for generating training data using a human link model, which enables the creation of a model that can estimate the state of a robot user without requiring the elderly user to stand up and perform other robot-assisted actions before use. Training data is generated using a link model and candidate centers of gravity, a simple method by which the state of the care robot user can be estimated, and physical support for standing, walking, and sitting can be provided. The effectiveness of the state estimation using the link model generated training data is verified off-line using sensor data independently obtained from the actual movements of the robot and user and also through experiments using an actual care robot. The results validated the state estimation since the time error was sufficiently short (0.35-1.85s), and the experiment confirmed that the robot could realize assistive actions with 90% accuracy.
... Some remarkable research results of walking assistance robots have been achieved by researchers, according to the different methods of walking assistance, the current walking assistance robots can be classified into several types, such as robotic walker [3,4], walking assistance exoskeleton [5,6], and intelligent walking cane [7,8]. In order to expand the function of intelligent walking assistance equipment, some researchers proposed multifunctional walking assistance robots. ...
To meet the walking demand of people who is less able to exercise, a foot-wheel cooperation walking assistance robot is designed, a control method of human-robot coordination movement is proposed, and then the walking on-the-wheel system is realized. Firstly, the structure of the foot-wheel cooperation walking assistance robot is designed, the kinematics of human lower limbs is analyzed, and the movement relationship between the foot system and wheel system is established. Secondly, the control methods of the foot system and wheel system are studied respectively, composite control method is used to realize the function that the motion of the human foot is followed by the pedal. Based on the user’s walking information and the motion relationship between the foot system and the wheel system, the coordinated motion control of the foot system and the wheel system is realized. Finally, an experimental prototype of foot-wheel cooperation walking assistance robot is developed, then the foot-wheel cooperation walking assistance experiment is completed. Experimental results show that the function of walking on the wheeled system can be realized by the proposed human-robot coordination movement method.
... • Omni-directional mobile base (OMB) comprises of three commercially available omni-wheels and actuators, which are specially designed for walker systems. A sixaxis force/torque sensor is used as the main control input interface and plays an important role in estimating the user's walking intention and detecting falls [45]. • SANBOT ELF consists of 51 sensors enabling interaction with its environment. ...
In recent decades, modern developed societies have experienced a significant increase in life expectancy, resulting in a significant degree of aging in the population. This demographic shift has had a significant impact on the daily needs and habits of the population. According to recent demographic projections, the elderly population is expected to triple and reach 2 billion people worldwide by 2050. However, future societies around the world are not adequately prepared to face the potential challenges arising from population aging. Elderly people tend to spend more time at home, but the functionalities and ergonomics of current home equipment and appliances do not fully satisfy their needs. Moreover, the absence of familiarity with new, smarter, and automated domestic technologies creates a significant gap that affects the acceptance and adoption of these technologies by the elderly. In this work, we present the most important technical challenges for the integration of assisted living technologies into a Mobile Robotic Platform (MRP). Additionally, we present the ASPiDA concept, a project proposing a holistic system to support elderly people in their domicile environment.
