Sensory integration for neuroprostheses: from functional benefits to neural correlates.

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

Upper limb intention tremor assessment: opportunities and challenges in wearable technology.

BACKGROUND: Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature. METHODOLOGY & RESULTS: This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table. CONCLUSIONS: Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

Grip Force Dynamics During Exoskeleton-Assisted and Virtual Grasping.

The grip force dynamics during grasping and lifting of diversely weighted objects are highly informative about an individual's level of sensorimotor control and potential neurological condition. Therefore, grip force profiles might be used for assessment and bio-feedback training during neurorehabilitation therapy. Modern neurorehabilitation methods, such as exoskeleton-assisted grasping and virtual-reality-based hand function training, strongly differ from classical grasp-and-lift experiments which might influence the sensorimotor control of grasping and thus the characteristics of grip force profiles. In this feasibility study with six healthy participants, we investigated the changes in grip force profiles during exoskeleton-assisted grasping and grasping of virtual objects. Our results show that a light-weight and highly compliant hand exoskeleton is able to assist users during grasping while not removing the core characteristics of their grip force dynamics. Furthermore, we show that when participants grasp objects with virtual weights, they adapt quickly to unknown virtual weights and choose efficient grip forces. Moreover, predictive overshoot forces are produced that match inertial forces which would originate from a physical object of the same weight. In summary, these results suggest that users of advanced neurorehabilitation methods employ and adapt their prior internal forward models for sensorimotor control of grasping. Incorporating such insights about the grip force dynamics of human grasping in the design of neurorehabilitation methods, such as hand exoskeletons, might improve their usability and rehabilitative function.

Damping TENS-Induced Essential Tremor Symptoms in Activities of Daily Living Using the TuMove Wrist Exoskeleton.

Essential Tremor (ET) is the most frequent movement disorder in adults. Upper-limb exoskeletons are a promising solution to alleviate ET symptoms. We propose a novel wrist exoskeleton for tremor damping. The TuMove exoskeleton is light-weight, portable, easy to use, and designed for ADLs and activities requiring hand dexterity. We validated the effectiveness of our exoskeleton by inducing forearm tremors using TENS on 5 healthy subjects. Our results show that wrist ranges are generally kept in most of the ROM needed in ADLs. The damping system reduced more than 30% of the tremor's angular velocity during drinking and pouring tasks. Furthermore, the completion time of the Archimedes spiral was decreased by 2.76 seconds (13.0%) and for the 9-Hole-Peg-Test by 2.77 seconds (11.8 %), indicating a performance improvement in dexterity tasks.