Haohan Zhang

Neck weakness limits head control and quality of life for individuals with Amyotrophic Lateral Sclerosis (ALS). The Utah Neck Exoskeleton can restore neck motion, but current control methods-joystick and gaze tracking-have limited accessibility and reliability. These preliminary offline analyses investigate neck electromyography (EMG) as an alternative control modality from ALS patients. EMG signals were recorded from four male participants with ALS while performing neck flexion/extension, axial rotation, and lateral deviation. The resulting dataset was used to train convolutional neural networks (CNNs) per patient to classify either head position or movement direction from EMG features offline. Position classification significantly outperformed direction classification, with a mean accuracy of 82.5% ± 0.010 across participants. Performance was consistent when controlling one, two, or all three neck degrees of freedom. A subset of participants with sufficient residual motor function also completed neck movements while talking or chewing. Classification accuracy decreased during talking and chewing, although these effects were not statistically significant. Importantly however, training CNNs with diverse data that included periods of talking and chewing improved algorithm robustness across all conditions. These findings suggest that neck EMG signals can reliably predict intended head movements in ALS, even in the presence of weak and often confounding muscle activity. Offline accuracy and real-time computational speed suggest the approach is feasible for future online user-in-the-loop studies. Altogether, this pilot work advances EMG-based assistive technology for individuals with severe motor impairments, laying the groundwork for clinically viable, intuitive control systems.

Neck muscle weakness causes the inability to raise and move the head, leading to fatigue, neck pain, and a “head-on-chest” posture (dropped head syndrome) in severe cases, which significantly affects quality of life. Static neck collars are the current standard of care. However, these collars are passive, which cannot restore the head-neck movement necessary for daily tasks. Emerging robotic devices like powered neck exoskeletons were developed to enable head-neck movements. Previous laboratory tests showed improved patients’ ability to follow prescribed trajectories; however, the ability to assist with daily tasks of such a robotic device remains unknown. In this paper, the functional range of motion allowed by a state-of-the-art powered neck exoskeleton was compared to a clinic-standard static neck collar in healthy adults performing simulated daily tasks wearing these devices. Results showed a greater head range of motion and consequently less compensatory torso movements while wearing the neck exoskeleton in its transparent mode. Participants rated the neck exoskeleton more favorably than the static collar in terms of comfort and ability to perform the tasks. Results also revealed the range of motion limits of the current neck exoskeleton for these daily tasks. These results provided justifications for using neck exoskeletons to restore daily functions and offered critical insights into future refinement of this technology to enable head range of motion for critical daily activities.

We describe a multimodal dataset of paired head and eye movements acquired in controlled virtual reality environments. Our dataset includes head and eye movement for n = 25 participants who interacted with four different virtual reality environments that required coordinated head and eye behaviors. Our data collection involved two visual tracking tasks and two visual searching tasks. Each participant performed each task three times, resulting in approximately 1080 seconds of paired head and eye movement and 129,611 data samples of paired head and eye rotations per participant. This dataset enables research into predictive models of intended head movement conditioned on gaze for augmented and virtual reality experiences, as well as assistive devices like powered exoskeletons for individuals with head-neck mobility limitations. This dataset also allows biobehavioral and mechanism studies of the variability in head and eye movement across different participants and tasks. The virtual environment developed for this data collection is open sourced and thus available for others to perform their own data collection and modify the environment.

Attaching a wearable device to the user's body for comfort and function while accommodating the differences and changes in body shapes often represents a challenge. In this letter, we propose an approach that addresses this problem through granular jamming, where a granule-filled membrane stiffens by rapidly decreasing the internal air pressure (e.g., vacuum), causing the granule material to be jammed together due to friction. This structure was used to conform to complex shapes of the human body when it is in the soft state while switching to the rigid state for proper robot functions by jamming the granules via vacuum. We performed an experiment to systematically investigate the effect of multiple design parameters on the ability of such jamming-based interfaces to hold against a lateral force. Specifically, we developed a bench prototype where modular granular-jamming structures are attached to objects of different sizes and shapes via a downward suspension force. Our data showed that the use of jamming is necessary to increase the overall structure stability by 1.73 to 2.16 N. Furthermore, using three modules, high suspension force, and a low membrane infill ($\sim$25%) also contribute to high resistance to lateral force. Our results lay a foundation for future implementation of wearable attachments using granular-jamming structures.

This letter presents a novel cable-driven exosuit intended for head-neck support and movement assistance. Mobility limitations in the head-neck, such as dropped head syndrome, can result from various neurological disorders. Current solutions, ranging from static neck collars to rigid-link robotic neck exoskeletons, are unsatisfactory. Neck collars are the most used clinically but fail to restore head-neck motion. Rigid-link neck exoskeletons can enable head movement but are bulky and restrictive. In this letter, we present the design of this exosuit, an analysis of its ability to balance the gravitational moment of the head in simulation, and the results of a user study comparing its kinematic performance to a state-of-the-art rigid-link neck exoskeleton. The exosuit is able to support the head across its full range of motion according to simulation results. It fits users of different sizes and participants exhibited more natural head-neck movement wearing the exosuit as compared to wearing the rigid-link exoskeleton. The exosuit allowed more head rotations than the rigid-link neck exoskeleton and required less compensatory torso movement for three daily tasks (looking for traffic, drinking from a bottle, and picking up an object from the floor). Its absolute range of motion was also much larger than the one allowed by the rigid-link neck exoskeleton. These results demonstrate the kinematic benefits of a cable-driven neck exosuit and provide justification for studying the use of such an exosuit for head-neck movement assistance in patient groups.

Neck muscle weakness due to amyotrophic lateral sclerosis (ALS) can result in dropped head syndrome, adversely impacting the quality of life of those affected. Static neck collars are currently prescribed to hold the head in a fixed upright position. However, these braces are uncomfortable and do not allow any voluntary head-neck movements. By contrast, powered neck exoskeletons have the potential to enable head-neck movements. Our group has recently improved the mechanical structure of a state-of-the-art neck exoskeleton through a weighted optimization. To evaluate the effect of the structural changes, we conducted an experiment in which patients with ALS were asked to perform head-neck tracking tasks while using the two versions of the neck exoskeleton. We found that the neck muscle activation was significantly reduced when assisted by the structurally enhanced design compared to no assistance provided. The improved structure also improved kinematics tracking performance, allowing users to better achieve the desired head poses. In comparison, the previous design did not help reduce the muscle effort required to perform these tasks and even slightly worsened the kinematic tracking performance. It was also found that biomechanical benefits gained from using the structurally improved design were consistent across participants with both mild and severe neck weakness. Furthermore, we observed that participants preferred to use the powered neck exoskeletons to voluntarily move their heads and make eye contact during a conversation task rather than remain in a fixed upright position. Each of these findings highlights the importance of the structural design of neck exoskeletons in achieving desired biomechanical benefits and suggests that neck exoskeletons can be a viable method to improve the daily life of patients with ALS.

This paper introduces a novel cable-driven robotic platform that enables six degrees-of-freedom (DoF) natural head–neck movements. Poor postural control of the head–neck can be a debilitating symptom of neurological disorders such as amyotrophic lateral sclerosis and cerebral palsy. Current treatments using static neck collars are inadequate, and there is a need to develop new devices to empower movements and facilitate physical rehabilitation of the head–neck. State-of-the-art neck exoskeletons using lower DoF mechanisms with rigid linkages are limited by their hard motion constraints imposed on head–neck movements. By contrast, the cable-driven robot presented in this paper does not constrain motion and enables wide-range, 6-DoF control of the head–neck. We present the mechatronic design, validation, and control implementations of this robot, as well as a human experiment to demonstrate a potential use case of this versatile robot for rehabilitation. Participants were engaged in a target reaching task while the robot applied both assistive and resistive moments on the head during the task. Our results show that neck muscle activation increased by 19% when moving the head against resistance and decreased by 28–43% when assisted by the robot. Overall, these results provide a scientific justification for further research in enabling movement and identifying personalized rehabilitation for motor training. Beyond rehabilitation, other applications such as applying force perturbations on the head to study sensory integration and applying traction to achieve pain relief may benefit from the innovation of this robotic platform which is capable of applying controlled 6-DoF forces/moments on the head.

This paper introduces a novel cable-driven robotic platform to assist with and train head-neck movements. Poor postural control of the head-neck can be a debilitating symptom of neurological disorders like amyotrophic lateral sclerosis and cerebral palsy. Current treatments using static neck collars are inadequate and there is a need to develop new devices to empower movements and facilitate physical rehabilitation of the head-neck. Existing exoskeletons using rigid linkages are limited by their restrictive structure. By contrast, the cable-driven robot presented in this paper does not constrain motion and allows for wide-range, six degrees-of-freedom control of the head-neck. We present the mechatronic design and control implementations of this robot, as well as a user study to demonstrate its feasibility to assist with head-neck motion and apply a resistive moment on the head using a target reaching task. Our results show that neck muscle activation increased by 19% when moving the head against a resistive force field and decreased by 28-43% when assisted by the robot in two different assistive control modes. Overall, these results provide a scientific justification for future design and control optimizations to enable movement and studies to identify personalized rehabilitation for motor training.

This paper presents a novel robotic system to characterize and retrain reaching in rats. This robot is intended to be a research platform for rehabilitation of forelimb movements in rats. In this paper, we focus on the design of this robotic system. We present the design requirements, mathematical models, and details of the physical device. A parallel mechanism with a special