Smart walkers: an application-oriented review

Low-force human-human hand interactions induce gait changes through sensorimotor engagement instead of direct mechanical effects

Physical human-robot interactions (pHRI) often provide mechanical force and power to aid walking without requiring voluntary effort from the human. Alternatively, principles of physical human-human interactions (pHHI) can inspire pHRI that aids walking by engaging human sensorimotor processes. We hypothesize that low-force pHHI can intuitively induce a person to alter their walking through haptic communication. In our experiment, an expert partner dancer influenced novice participants to alter step frequency solely through hand interactions. Without prior instruction, training, or knowledge of the expert's goal, novices decreased step frequency 29% and increased step frequency 18% based on low forces (< 20 N) at the hand. Power transfer at the hands was 3-700 × smaller than what is necessary to propel locomotion, suggesting that hand interactions did not mechanically constrain the novice's gait. Instead, the sign/direction of hand forces and power may communicate information about how to alter walking. Finally, the expert modulated her arm effective dynamics to match that of each novice, suggesting a bidirectional haptic communication strategy for pHRI that adapts to the human. Our results provide a framework for developing pHRI at the hand that may be applicable to assistive technology and physical rehabilitation, human-robot manufacturing, physical education, and recreation.

Adaptability of Assistive Mobility Devices and the Role of the Internet of Medical Things: Comprehensive Review

Background

With the projected upsurge in the percentage of people with some form of disability, there has been a significant increase in the need for assistive mobility devices. However, for mobility aids to be effective, such devices should be adapted to the user’s needs. This can be achieved by improving the confidence of the acquired information (interaction between the user, the environment, and the device) following design specifications. Therefore, there is a need for literature review on the adaptability of assistive mobility devices.

Objective

In this study, we aim to review the adaptability of assistive mobility devices and the role of the internet of medical things in terms of the acquired information for assistive mobility devices. We review internet-enabled assistive mobility technologies and non–internet of things (IoT) assistive mobility devices. These technologies will provide awareness of the status of adaptive mobility technology and serve as a source and reference regarding information to health care professionals and researchers.

Methods

We performed a literature review search on the following databases of academic references and journals: Google Scholar, ScienceDirect, Institute of Electrical and Electronics Engineers, Springer, and websites of assistive mobility and foundations presenting studies on assistive mobility found through a generic Google search (including the World Health Organization website). The following keywords were used: assistive mobility OR assistive robots, assistive mobility devices, internet-enabled assistive mobility technologies, IoT Framework OR IoT Architecture AND for Healthcare, assisted navigation OR autonomous navigation, mobility AND aids OR devices, adaptability of assistive technology, adaptive mobility devices, pattern recognition, autonomous navigational systems, human-robot interfaces, motor rehabilitation devices, perception, and ambient assisted living.

Results

We identified 13,286 results (excluding titles that were not relevant to this study). Then, through a narrative review, we selected 189 potential studies (189/13,286, 1.42%) from the existing literature on the adaptability of assistive mobility devices and IoT frameworks for assistive mobility and conducted a critical analysis. Of the 189 potential studies, 82 (43.4%) were selected for analysis after meeting the inclusion criteria. On the basis of the type of technologies presented in the reviewed articles, we proposed a categorization of the adaptability of smart assistive mobility devices in terms of their interaction with the user (user system interface), perception techniques, and communication and sensing frameworks.

Conclusions

We discussed notable limitations of the reviewed literature studies. The findings revealed that an improvement in the adaptation of assistive mobility systems would require a reduction in training time and avoidance of cognitive overload. Furthermore, sensor fusion and classification accuracy are critical for achieving real-world testing requirements. Finally, the trade-off between cost and performance should be considered in the commercialization of these devices.

Gait Phase Estimation Based on User–Walker Interaction Force

Smart walkers have been developed for assistance and rehabilitation of elderly people and patients with physical health conditions. A force sensor mounted under the handle is widely used in smart walkers to establish a human–machine interface. The interaction force can be used to control the walker and estimate gait parameters using methods such as the Kalman filter for real-time estimation. However, the estimation performance decreases when the peaks of the interaction force are not captured. To improve the stability and accuracy of gait parameter estimation, we propose an online estimation method to continuously estimate the gait phase and cadence. A multiple model switching mechanism is introduced to improve the estimation performance when gait is asymmetric, and an adaptive rule is proposed to improve the estimation robustness and accuracy. Simulations and experiments demonstrate the effectiveness and accuracy of the proposed gait parameter estimation method. Here, the average estimation error for the gait phase is 0.691 rad when the gait is symmetric and 0.722 rad when it is asymmetric.

Evaluation of Physical Interaction during Walker-Assisted Gait with the AGoRA Walker: Strategies Based on Virtual Mechanical Stiffness

Smart walkers are commonly used as potential gait assistance devices, to provide physical and cognitive assistance within rehabilitation and clinical scenarios. To understand such rehabilitation processes, several biomechanical studies have been conducted to assess human gait with passive and active walkers. Several sessions were conducted with 11 healthy volunteers to assess three interaction strategies based on passive, low and high mechanical stiffness values on the AGoRA Smart Walker. The trials were carried out in a motion analysis laboratory. Kinematic data were also collected from the smart walker sensory interface. The interaction force between users and the device was recorded. The force required under passive and low stiffness modes was 56.66% and 67.48% smaller than the high stiffness mode, respectively. An increase of 17.03% for the hip range of motion, as well as the highest trunk’s inclination, were obtained under the resistive mode, suggesting a compensating motion to exert a higher impulse force on the device. Kinematic and physical interaction data suggested that the high stiffness mode significantly affected the users’ gait pattern. Results suggested that users compensated their kinematics, tilting their trunk and lower limbs to exert higher impulse forces on the device.

The effect of horizontal forces from a Smart Walker on gait and perceived exertion

Increasingly, electric motors are being incorporated into wheeled walkers to implement various smart features to better assist their users physically. These modified walkers, known as Smart Walkers, use their electric motors to generate horizontal forces that can be used to reduce the physical load for walking, prevent falls and provide navigation support. However, these forces can also alter gait and may inadvertently increase the exertion of the users. This study aims to describe the effects of assistive and resistive horizontal forces (from -18.47 N to 27.70 N) from a Smart Walker on gait and perceived exertion of its users during steady-state walking. Self-selected comfortable walking speed, cadence, stride length, double support phase and ratings of perceived exertion (RPE) were significantly affected and different effects were found for resistive force, relatively low assistive force and high assistive force. With increasing force from -18.47 N to 0 N, RPE decreased and the users walked with lower double support time. From 0 N to 9.23 N, RPE continued to decrease to its lowest point while gait parameters remained constant. Further increasing force up to 27.70 N increased RPE and led to the users to choose to walk at higher speeds. This study demonstrates that users adapt their gait significantly to the forces applied and relatively high constant forces, whether assistive or resistive, will increase perceived exertion. Hence, these need to be carefully considered when developing Smart Walkers in order to provide safe and effective support to its users.

Smart and Assistive Walker - ASBGo: Rehabilitation Robotics: A Smart-Walker to Assist Ataxic Patients

Locomotion is an important human faculty that affects an individual's life, bringing not only physical and psychosocial implications but also heavy social-economic consequences. Thus, it becomes paramount to find means (augmentative/assistive devices) to empower the user's residual capacities and promote functional recovery.In this context, a smart walker (SW) is explored for further clinical evaluation of ataxic patients during walker-assisted and to serve as a functional compensation and assist-as-needed personalized/customized rehabilitation tool, autonomously adapting assistance to the users' needs, through innovative combination of real-time multimodal sensory information from SW built-in sensors. To meet the users' needs, its design was weighed, considering to whom it is intended.Thereby, this paper presents the system overview, focusing on design considerations, mechanical structure (frame and main components), electronic and mechatronic components, followed by its functionalities. Lastly, it presents results regarding the main functionalities, addressing clinical evidence.

Evaluating the sit-to-stand transfer assistance from a smart walker in older adults with motor impairments

AIM

To evaluate the effectiveness and user satisfaction with the sit-to-stand (STS) assistance system of a smart walker (SW), and to identify factors associated with them in potential users.

METHODS

A total of 33 older adults (29 women, aged ≥65 years) with motor impairments (habitual rollator use) and no severe cognitive impairment (Mini-Mental State Examination ≥17 points) carried out a Five-Chair Stand Test without assistance and five STS transfers with the STS assistance system. Based on the number of successfully completed STS transfers, success rates were calculated for the Five-Chair Stand Test and the SW-assisted STS transfers, and compared using the Wilcoxon signed-rank test. User satisfaction was assessed using the Tele-healthcare Satisfaction Questionnaire-Wearable Technology (0-80 points, higher score = higher satisfaction). Bivariate correlations and multiple linear regression analyses were used to identify participant characteristics associated with the success rate and user satisfaction with the STS assistance system.

RESULTS

The success rate for the SW-assisted STS transfers was significantly higher than for the Five-Chair Stand Test (93.3 ± 12.9% vs 54.5 ± 50.6%, P < 0.001). User satisfaction was high (Tele-healthcare Satisfaction Questionnaire-Wearable Technology 62.5 ± 11.2 points). The success rate with the STS assistance system was not significantly associated with any participant characteristics. Higher body mass index was a significant independent predictor of higher user satisfaction.

CONCLUSIONS

The SW-integrated STS assistance system can provide effective STS support with high user satisfaction for a wide range of potential users. Our findings suggest the high potential of the STS assistance system for promoting mobility, independence and quality of life for older adults with motor impairments. Geriatr Gerontol Int 2020; 20: 312-316.

A Novel Multimodal Cognitive Interaction for Walker-Assisted Rehabilitation Therapies

This work presents a multimodal cognitive interaction strategy aiming at walker-assisted rehabilitation therapies, with special focus on post-stroke patients. Such interaction strategy is based on monitoring user's gait and face orientation to command the displacement of the smart walker. Users are able to actively command the steering of the walker by changing their face orientation, while their lower limbs movement affect the walker's linear velocity. The proposed system is validated using a smart walker and the results obtained point to the feasibility of employing such cognitive interaction in rehabilitation therapies.

Identifying the Effects of Assistive and Resistive Guidance on the Gait of Elderly People Using a Smart Walker

Progression of technology has expanded applications of smart walkers in clinical fields. However, it is essential to investigate the effects of different types of gait guidance in order to introduce smart walkers more widely throughout these fields. The purpose of this study was to identify the effects of assistive and resistive guidance on the gait of elderly people using a smart walker. Gait parameters, surface electromyography of lower limb muscles, and trunk acceleration were measured. The assistive guidance force significantly increased gait speed, step length, and cadence while increasing trunk acceleration variability. The same amount of resistive guidance force did not change gait parameters; instead, however, it restrained the speed-dependent increase of trunk acceleration variability in the mediolateral direction. An analysis of muscle activity suggested that the lower limb muscle activity could be increased by varying gait parameters including speed, step length, and cadence.

High mobility control of an omnidirectional platform for gait rehabilitation after stroke

We present a novel control method for an omnidirectional robotic platform for gait training. This mobile platform or "walker" provides trunk support and allows unrestricted motion of the pelvis simultaneously. In addition to helping the user maintain balance and preventing falls, the walker combines two types of therapeutic intervention: forward propulsion of the trunk and partial body weight support (BWS). The core of the walker's control is an admittance controller that maximizes the platform's horizontal mobility by optimizing the virtual mass of the admittance model. Said mass represents the best tradeoff between a low-frequency oscillation mode that becomes more damped as the virtual mass decreases, and a high-frequency mode that becomes less damped simultaneously and hence could destabilize the system. Forward propulsion of the trunk is aided by a horizontal force that is modulated with the patient's gait speed and turning rate to ensure easy adaptation. BWS is provided by a second, independent admittance controller that generates a spring-like upward force. In an initial study, a stroke patient was able to walk stably in the platform, as evidenced by the absence of oscillations associated with an excessively low virtual mass. A progressive increase in the patient's self-selected speed, along with greater uniformity in the instantaneous velocity, suggest that forward propulsion was effective in compensating the patient's own propulsion deficit.