Integrating Tactile Feedback Technologies Into Home-Based Telerehabilitation: Opportunities and Challenges in Light of COVID-19 Pandemic

Handelzalts, Shirley; Ballardini, Giulia; Avraham, Chen; Pagano, Mattia; Casadio, Maura; Nisky, Ilana

doi:10.3389/fnbot.2021.617636

REVIEW article

Front. Neurorobot., 17 February 2021

Volume 15 - 2021 | https://doi.org/10.3389/fnbot.2021.617636

Integrating Tactile Feedback Technologies Into Home-Based Telerehabilitation: Opportunities and Challenges in Light of COVID-19 Pandemic

1. Department of Physical Therapy, Ben-Gurion University of the Negev, Be'er Sheva, Israel
2. The Translational Neurorehabilitation Lab at Adi Negev Nahalat Eran, Ofakim, Israel
3. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
4. S.C.I.L Joint Lab, Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), Santa Corona Hospital, Pietra Ligure, Italy
5. Department of Biomedical Engineering, Ben-Gurion University of the Negev, Be'er Sheva, Israel
6. Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Be'er Sheva, Israel

Abstract

The COVID-19 pandemic has highlighted the need for advancing the development and implementation of novel means for home-based telerehabilitation in order to enable remote assessment and training for individuals with disabling conditions in need of therapy. While somatosensory input is essential for motor function, to date, most telerehabilitation therapies and technologies focus on assessing and training motor impairments, while the somatosensorial aspect is largely neglected. The integration of tactile devices into home-based rehabilitation practice has the potential to enhance the recovery of sensorimotor impairments and to promote functional gains through practice in an enriched environment with augmented tactile feedback and haptic interactions. In the current review, we outline the clinical approaches for stimulating somatosensation in home-based telerehabilitation and review the existing technologies for conveying mechanical tactile feedback (i.e., vibration, stretch, pressure, and mid-air stimulations). We focus on tactile feedback technologies that can be integrated into home-based practice due to their relatively low cost, compact size, and lightweight. The advantages and opportunities, as well as the long-term challenges and gaps with regards to implementing these technologies into home-based telerehabilitation, are discussed.

Introduction

The COVID-19 pandemic highlights the need to accelerate the development and implementation of innovative approaches for home-based rehabilitation (Simpson and Robinson, 2020). While in normal, non-pandemic times many individuals in need of rehabilitation services do not receive sufficient therapy due to difficulties posed by the need to travel to the location where the therapy is provided, a shortage of regional rehabilitation care, and poor adherence to assignments (Cramer et al., ), the COVID-19 pandemic is presenting new challenges to rehabilitation services. The restrictions imposed to contain the spread of infection further limit access to rehabilitation services (Chaler et al., ) and challenge societal well-being. This may lead to long-term negative consequences by increasing functional impairments, and reducing participation and quality of life (Boldrini et al., ). Telerehabilitation from home may partially mitigate these challenges, but state of the art telerehabilitation systems often only use visual or/and auditory feedback and lack somatosensory feedback (Navarro et al., 2018).

Somatosensory input is essential for accurate motor control and interactions with the external world (Pearson, 2000; Perez et al., 2003; Borich et al., ). The somatosensory impairment that is observed in many neurological disorders such as stroke, traumatic brain injury, and spinal cord injury can lead to impairments in adjusting the amount of force applied during grasping and fine manipulation of objects (Sullivan and Hedman, 2008; Doyle et al., , ; Connell et al., ; Hill et al., 2014) and in performing tasks that require rapid dextrous movements (Goebl and Palmer, 2008), as well as in controlling more gross functions such as gait and posture (Maki and McIlroy, 1997; Horak, 2006).

In in-person rehabilitation intervention therapists frequently use touch to assist, and to provide and perceive information, as well as to comfort and encourage patients (Roger et al., 2002). In a survey regarding satisfaction with telerehabilitation during the COVID-19 pandemic, the absence of touch was reported by patients as a limitation (Tenforde et al., 2020). The current review focuses on tactile technologies that can be used as innovative solutions to support home-based telerehabilitation and addresses some challenges that have become more salient during the COVID-19 pandemic.

Previous reviews discussed telerehabilitation and wearable haptic devices; however, none has provided a comprehensive perspective on the variety of tactile stimulation technologies and the ways to exploit them for home-based telerehabilitation. An overview on tactile displays was conducted by Jones and Sarter (2008); however, since then significant developments in tactile technology have been presented. Culbertson et al. () reviewed the design, control, and general applications of haptic devices, but did not focus on rehabilitation applications. Several reviews focused on wearable technologies (not necessarily haptics) that can be used for remote monitoring of physiological and kinematic measurements, with a brief overview on the applications for home-based rehabilitation (Patel et al., 2012; Wang et al., 2017). Navarro et al. (2018) proposed features related to adaptive, multisensorial, physiological and social aspects that should be considered in the development process of the next generation of telerehabilitation systems. A systematic review of virtual reality technologies for rehabilitation examined the effect of haptic feedback on motor performance (Rose et al., 2018). Another review (Shull and Damian, 2015) examined wearable haptic applications for a variety of sensory impairments; however, the focus of that review was on stimulations to enhance motor performance. A previous narrative review focused on tactile technologies for hand rehabilitation in central nervous system disorders (Demain et al., ). In this work, we extend previous reviews by covering the development in tactile technologies over the last decade with an emphasis on wearable devices that potentially could be utilized at home. We also expand the scope to include the assessment of somatosensory deficits, in addition to various rehabilitative applications, and address the recent developments in mediation of social interaction. Specifically, we review: (1) clinical approaches for stimulating somatosensation in home-based rehabilitation, (2) tactile technologies that can be integrated into home-based rehabilitation, and (3) the challenges and gaps, as well as the opportunities, in this field.

Clinical Approaches for Stimulating Somatosensation in Home-Based Neurorehabilitation

Providing Tactile Augmented Feedback to Enhance Motor Control Performance and Learning

Somatosensory augmented feedback provides additional sensory cues that complement and/or replace native sensory input from the somatosensory, visual, and/or vestibular systems (Bach-y-Rita and Kercel, ). Tactile cues can guide patients on how to improve their movements (Bark et al., ) and may assist them in achieving their goals more quickly and/or more easily (Magill, 2004). A promising application of tactile feedback is to provide patients with guidance on how to improve their movements without the constant presence of a therapist (Bark et al., ; Bao et al., ), including when practicing on their own. The augmented feedback can be triggered by the participant's motor performance and can provide information continuously during the action or at specified times (Ferris and Sarter, ; Galambos, 2012; Kaul and Rohs, 2017). Compared with visual feedback, real time tactile feedback makes it possible for patients to receive information regarding movement errors without the need to shift visual attention, thus affording a more “natural” movement (Bark et al., ).

Tactile stimulation can also be beneficial even if it does not provide any information. For instance, subthreshold tactile stimulations (i.e., below the level at which a person can perceive the stimulation) add noise to proprioceptive signals and might help these signals to overcome the threshold of specific neural circuits. This phenomenon, also known as the stochastic resonance theory (Gammaitoni, 1995; Gammaitoni et al., 1998; Moss et al., 2004), facilitates more efficient detection of somatosensory information, and improves sensorimotor performance (Collins et al., , ). As such, it could be used in the rehabilitation of individuals with sensorimotor deficits to improve motor functions (e.g., grasp, object manipulation, balance and gait) and tactile sensation (Enders et al., ; Seo et al., 2014, 2019).

Applying Tactile Stimulations to Improve/Restore Cutaneous Somatosensation

Somatosensory impairment is considered to have a negative prognostic impact on rehabilitation interventions and overall motor function recovery (Bowerman et al., ; Dietz and Fouad, ; Zandvliet et al., 2020). Although the current literature in this field is limited, a recent systematic review and meta-analysis indicated positive effects in improving somatosensory impairments (Serrada et al., 2019). Specifically, sensory discrimination training by repeated practice to distinguish textures and localize tactile stimuli can influence the sensory system and drive recovery (Carey et al., ; Yekutiel and Guttman, 1993; Turville et al., 2019).

Presenting Tactile Feedback in Virtual Reality Environments

Telerehabilitation is often based on virtual reality systems and interactive video games that aim to facilitate repetitions of movements and to make the repetitive exercises more engaging, enjoyable and motivating (Standen et al., 2015). The virtual experience can be further enhanced by using tactile devices that can convey haptic interactions between the user and the virtual objects (Galambos, 2012; Culbertson et al., ).

Conveying Social Tactile Interaction

Haptic feedback plays a critical role in emotional and social communication (Strong and Gaver, 1996; Brave and Dahley, ). During in-person rehabilitation sessions therapists often use touch to comfort and encourage patients (Roger et al., 2002). Recent developments in wearable tactile devices demonstrate very promising results in conveying sensations such as comfort and affection (Culbertson et al., ; Nunez et al., 2019, 2020), attention (Baumann et al., ), playfulness (Mullenbach et al., 2014), or social presence (Baldi et al., ). The integration of social tactile aspects into telerehabilitation systems would open new possibilities for remote therapist-patient communication and may facilitate wider adoption of telerehabilitation from home by patients.

Assessing Tactile Impairments

In addition to the above training strategies, the use of measures to quantify somatosensory deficits could help therapists to understand patients' impairments beyond motor and functional status and assist in targeting appropriate interventions. The assessment of somatosensory functions, including proprioception and sensitivity to light touch, pressure, and temperature, cannot be done remotely in the traditional way where the therapist applies the stimulation and evaluates the performance using scales. Portable, and often wearable devices that apply multimodal stimulations have the potential to provide reliable and quantitative information regarding somatosensory impairments in a home-based setting (Rinderknecht et al., 2015, 2019). Such portable devices have already been used in some virtual reality systems for baseline measurements of activity and kinematics and for tracking changes over time (Patel et al., 2012; Chen et al., ; Bortone et al., ).

Tactile Stimulation Technologies

Over the last few decades, technologies that can provide versatile tactile stimulations have become very popular and many new devices continue to be developed. These devices can be integrated into wearable technologies and utilized for telerehabilitation due to their low cost, compact size, and lightweight. From the technological point of view, there is a variety of ways to apply tactile stimulation. These can be categorized according to the mechanism evoking the tactile sensation: mechanical, electrotactile, and thermal. In order to provide an in depth review of the technology and its applications, in this review we focus on mechanical tactile stimulations. However, it should be noted that electrotactile stimulation is also used for various assistive technologies and rehabilitation applications such as for people with visual (Bliss et al., ; Kajimoto et al., 2001) and auditory impairments (Weisenberger et al., 1989), as well as in prostheses, orthoses (Schweisfurth et al., 2016; Svensson et al., 2017) and stroke rehabilitation (for a review see Laufer and Elboim-Gabyzon, 2011).

Mechanical tactile stimulations can be further divided into vibration, skin deformation, and mid-air stimulations. Recently the idea of wearable tactile devices that combine vibration, stretch, and pressure for conveying multimodal haptic information was introduced (Aggravi et al., ; Sullivan et al., 2019; Dunkelberger et al., ), highlighting the importance of understanding the unique properties of each stimulation type and harnessing the advantages of each to design devices that are more than the sum of their parts. In the remainder of this section, we review the state of the art in mechanical tactile stimulation devices. For each type of device we review the technology, its applications for healthy and patient populations, and its advantages and disadvantages. The different devices and studies are summarized in Tables 1, 2. Table 1 summarizes the devices by stimulation type, actuator type, technological maturity level, and application. We rank the technological maturity level based on how extensively testing of the device has been reported in the literature, with the following levels: prototype demonstration (N < 10); healthy user studies (N = 10–100); extensive healthy user studies (N > 100); patient user studies (N = 10–100); extensive patient user studies (N > 100). Table 2 summarizes the studies that were reviewed here that were tested on patient populations for different rehabilitation applications.

Table 1

Stimulation type	Device type	Device maturity level	Applications	Commercial availability
Vibration	Single actuator	Extensive healthy and patient user studies	Improve walking pattern (Janssen et al., 2009)	BalanceFreedom of SwayStar system https://www.b2i.info/web/index.htm
			Improve force control accuracy (Ahmaniemi, )
			Convey proprioceptive information (Bark et al., )
	Multiple actuators	Extensive healthy and patient user studies	Enhance motor learning and performance (Lieberman and Breazeal, 2007; Bark et al., ; Kaul and Rohs, 2017; Van Breda et al., 2017; Shah et al., 2018)
			Guide movement direction (Van Erp et al., 2005; Krueger et al., 2017; Risi et al., 2019)
			Improve standing balance (Lee et al., 2012; Ma and Lee, 2017; Ballardini et al., )	Vertiguard RT https://zeisberg.net/posturographie.html
			Improve walking pattern (Chen B. et al., ; Wan et al., 2016; Muijzer-Witteveen et al., 2017; Xu et al., 2017)
			Convey various types of information (Ferris and Sarter, ; Cobus et al., )
			Convey affective touch (Israr and Abnousi, 2018)
			Assess somatosensory impairments (Tommerdahl et al., 2019)	Brain Gauge https://www.corticalmetrics.com/howitworks
	Multiple actuators on a glove	Healthy and patient user studies	Convey virtual objects information (Muramatsu et al., 2012)	CyberTouch http://www.cyberglovesystems.com/cybertouch2
			Convey force information (Galambos, 2012)
			Assess somatosensory impairments (Rinderknecht et al., 2015, 2019)
	Single actuator with multiple probes	Healthy user studies	Assess somatosensory impairments (Holden et al., 2012; Puts et al., 2013; Mikkelsen et al., 2020)
Skin deformation—tangential and stretch	Tactor	Extensive healthy user studies and patient studies	Alter mechanical properties of virtual objects (Sylvester and Provancher, 2007; Quek et al., 2013, 2014b; Schorr et al., 2013; Farajian et al., ,)
			Convey direction information (Bark et al., ; Guinan et al., 2012, 2013a,b; Norman et al., 2014; Chinello et al., ; Kanjanapas et al., 2019)
			Convey information about curvature (Frisoli et al., ; Prattichizzo et al., 2013), weight (Kato et al., 2016; Choi et al., ), and virtual objects information (Yem and Kajimoto, 2017; Wang et al., 2020)
			Improve object manipulation (Leonardis et al., 2017; Schorr and Okamura, 2017b; Bortone et al., ), tracking (Quek et al., 2014b), insertion (Quek et al., 2015b), palpation (Schorr et al., 2015) and grasping (Westebring van der Putten et al., 2010; Kim and Colgate, 2012; Quek et al., 2015a; Choi et al., ; Stephens-Fripp et al., 2018; Avraham and Nisky, ; Bitton et al., ; Farajian et al., )
			Guide movement direction (Bark et al., ; Guinan et al., 2012, 2013a,b; Norman et al., 2014; Chinello et al., )
			Improve standing balance (Hur et al., 2019)
			Convey affective touch (Nunez et al., 2019)
			Assess somatosensory impairments (Ballardini et al., )
	Adhesive rings	Healthy user studies	Convey affective touch (Haynes et al., 2019)
	Belt/Vest	Healthy user studies	Substitute and augment force and torque feedback (Pacchierotti et al., 2016), convey sensation of mass (Minamizawa et al., 2007), and sensation of virtual objects (Minamizawa et al., 2008),
			Convey direction information (Bianchi, )
			Provide feedback about grasping force (Casini et al., )
			Guide movement direction (Stanley and Kuchenbecker, 2012; Pezent et al., 2019; Smith et al., 2020) and convey path information (Kumar et al., 2017)
			General tactile stimulation (Nakamura and Jones, 2003; Wu et al., 2010)
	Rocker and roller	Healthy user studies	Enhance virtual object manipulation (Provancher et al., 2005)
			Convey proprioceptive information (Battaglia et al., and 2019; Colella et al., ) (Clark et al., )
	Mechanical cranks	Healthy user studies	General tactile stimulation (Stephens-Fripp et al., 2018)
Skin deformation—pressure	Indentator	Healthy and patient user studies	General tactile stimulations (Chinello et al., )
			Convey sensations of softness (Frediani and Carpi, ), and holding a virtual object (Merrett et al., 2011)
			Convey direction information (Raitor et al., 2017; Agharese et al., )
			Render shape information of remote and virtual objects (Chinello et al., )
			Convey affective touch (Culbertson et al., )
			Assess somatosensory impairments (Jacobs et al., 2000)
	Belt	Prototype demonstration	Convey affective touch (Prattichizzo et al., 2010)
	Pin array	Healthy and patient user studies	Create 2D and 3D graphic display (Shimizu et al., 1993; Leo et al., 2016; Brayda et al., )
			General tactile stimulations (Caldwell et al., ),
			Convey sensations of roughness (Kim et al., 2009), and texture (Sarakoglou et al., 2005; Kyung and Park, 2007; Garcia-Hernandez et al., 2011)
Skin deformation or vibration ultrasound	Mid-air technology using phased arrays	Extensive healthy user studies	Create 3D haptic shapes (Long et al., 2014; Vo and Brewster, 2015; Makino et al., 2016)	UltraLeap https://www.ultraleap.com/
			Convey affective touch (Shakeri et al., 2017, 2018)

Tactile stimulation devices by type, maturity level, and applications in healthy individuals.

Maturity level is ranked by the following levels: prototype demonstration (N < 10); healthy user studies (N = 10–100); extensive healthy user studies (N > 100); patient user studies (N = 10–100); extensive patient user studies (N > 100). Note that the applications column refers to studies in healthy individuals; for types of devices that were also tested on patients please refer to Table 2 for more detailed information about the specific studies. Commercial availability of devices that were reviewed in the current paper and tested either on healthy or patient populations.

Table 2

Application	Population	Tested in a home setting (Yes/No)	Type of stimulation	Type of device	Wearable/ Non-wearable	References
Enhance upper extremity function	Multiple Sclerosis (N = 24)	No	Vibration	Multiple actuators	Wearable	Jiang et al., 2009
	Stroke (N = 12)	No	Subthreshold vibration	Single actuator, (TheraBracelet)	Wearable	Seo et al., 2019
Enhance gait and balance control	Stroke (N = 8)	No	Vibration	Multiple actuators	Wearable	Afzal et al.,
	Stroke (N = 17)	No	Vibration	Multiple actuators	Wearable	Yasuda et al., 2017
	Stroke (N = 3)	No	Vibration	Platform (The Rutgers Ankle Haptic Interface)	Non-wearable	Boian et al.,
	Stroke (N = 20)	No	Vibration	Multiple actuators	Wearable	Jaffe et al., 2004
	Parkinson's disease (N = 43)	No	Vibration	Single actuator (VibroGait)	Wearable	Fino and Mancini,
	Parkinson's disease (N = 20)	No	Vibration	Multiple actuators (BalanceFreedom)	Wearable	Nanhoe-Mahabier et al., 2012
	Parkinson's disease (N = 16)	No	Pressure	Steel stick	Non-wearable	Barbic et al.,
	Parkinson's disease (N = 10)	No	Vibration	Multiple actuators (Vertiguard)	Wearable	Rossi-Izquierdo et al., 2013
	Parkinson's disease (N = 9) and older adults at high risk for falls (N = 8) and older adults (N = 10)	No	Vibration	Multiple actuators	Wearable	High et al., 2018
	Parkinson's disease (N = 9) and older adults (N = 9)	No	Vibration	Multiple actuators	Wearable	Lee et al., 2018
	Older adults (N= 12)	Yes	Vibration	Multiple actuators	Wearable	Bao et al.,
	Peripheral Neuropathy (N = 4)	No	Pressure	Ballon arrays	Wearable	McKinney et al., 2014
	Vestibular disorder (N = 6)	No	Vibration	Multiple actuators	Wearable	Sienko et al., 2012
	Vestibular disorder (N = 7)	No	Vibration	Multiple actuators	Wearable	Sienko et al., 2013
	Vestibular disorder (N = 13)	No	Vibration	Multiple actuators (Vertiguard)	Wearable	Brugnera et al.,
	Vestibular disorder (N = 8)	No	Vibration	Multiple actuators	Wearable	Bao et al.,
	Vestibular disorder (N = 105)	No	Vibration	Multiple actuators, (Vertiguard)	Wearable	Basta et al.,
Enhance tactile sensation	Stroke (N = 5), diabetic neuropathy (N = 8) and older adults (N = 12)	No	Subthreshold vibration	Single actuator	Non-wearable	Liu et al., 2002
	Stroke (N = 10)	No	Subthreshold vibration	Single actuator	Wearable	Enders et al.,
	Stroke (N = 16)	Yes	Vibration	Multiple actuators on a glove	Wearable	Seim et al., 2020b
	Digital nerve injuries (N = 49)	No	Pressure	Rotating disk and a card	Non-wearable	Cheng,
	Chronic pain (N = 13)	No	Pressure	Probe	Non-wearable	Moseley et al., 2008
	Spinal cord injury (N = 7)	Yes	Vibration	Multiple actuators on a glove (Mobile Music Touch)	Wearable	Estes et al.,
Somatosensory assessment	Stroke (N= 2)	No	Vibration	Multiple actuators on a glove (ReHaptic Glove)	Wearable	Rinderknecht et al., 2019
	Stroke (N = 3)	No	Skin stretch	Tactor	Non-wearable	Ballardini et al.,
	Brain injury (N = 1)	No	Vibration	Multiple actuators (Brain Gauge)	Non-wearable	King et al., 2018
Enhance interaction realism in virtual reality environment	Children with neuromotor impairments (N = 20)	No	Skin stretch and pressure	Tactor	Wearable	Bortone et al.,
	Spinal cord injury (N = 9)	No	Vibration	Multiple actuators on a glove (CyberTouch)	Wearable	Dimbwadyo-Terrer et al.,

Tactile device applications for rehabilitation.

Vibration

Vibration is the simplest and most common tactile stimulation technology that has become ubiquitous and is used in a wide variety of devices such as phones, watches, games, and home appliances (Culbertson et al., ). Typically, the actuators used in wearable devices produce vibration at frequencies above 100 Hz, which activates the Pacinian corpuscles mechanoreceptors (Culbertson et al., ). The most common locations for applying the vibrotactile stimulation are the arm (Bark et al., ; Huisman et al., 2013; Krueger et al., 2017; Shah et al., 2018; Risi et al., 2019) and the torso (Van Erp et al., 2005; Lee et al., 2012; Ballardini et al., ). Other locations for stimulation include the hand (Jiang et al., 2009; Wan et al., 2016) and different locations on the lower limb (Chen B. et al., ; Shi et al., 2019). The design of the device and the stimulation patterns (e.g., frequency and amplitude of the vibration) need to take into account the targeted dermatomes and the density and size of the mechanoreceptors' receptive fields which vary across the body (Jones and Sarter, 2008; Johansson and Flanagan, 2009; Shah et al., 2019) and across the skin type (e.g., hairy skin has a reduced number of Pacinian corpuscles compared to glabrous skin) (Colgate and Brown, ; Ackerley et al., ). Skin type can also influence the quality of stimulation via its mechanical properties and its physical propagation of the vibration (Dandu et al., ; Hachisu and Suzuki, 2019).

Technology

Vibrotactile feedback can be conveyed by a single actuator, or by an array of actuators that create an oscillating movement. The choice of the actuator affects the size, shape, cost, availability, robustness, speed of response, input requirements, and power consumption of the device (Choi and Kuchenbecker, ). An overview of the different actuators can be found in Choi and Kuchenbecker () and Kern (2009).

The stimulation patterns can be divided into two fundamental categories: (1) binary on-off state, and (2) continuous vibration, created by changing parameters of the vibration signals such as amplitude, frequency, duration, rhythm, and waveform (Brewster and Brown, ; Jones and Sarter, 2008). Binary feedback is not continuously provided but is triggered by specific events such as an alarm or event-cue related information (Ferris and Sarter, ; Galambos, 2012; Kaul and Rohs, 2017). The vibration intensity can be constant or may vary according to the event (Cobus et al., ). Continuous vibrotactile stimulation is used to convey various types of information to the users, including: (1) state feedback, encoding position and/or velocity of limbs (Ferris and Sarter, ; Krueger et al., 2017; Shah et al., 2018; Risi et al., 2019), (2) force feedback, encoding the amount of force exerted (Ahmaniemi, ), and (3) error feedback, encoding information regarding the goal of the task and the state of the end-effector (Wall et al., 2001; Cuppone et al., ; Krueger et al., 2017).

By controlling the shape and timing of the signals from multiple static actuators, it is also possible to display illusions of movement that can enrich the design space of tactile stimulation. Prominent examples are: (1) phi (or beta) movement, where a smooth apparent motion of a single stimulus is created by the periodic activation of two spatially separated stimuli (Sherrick and Rogers, 1966; Lederman and Klatzky, 2009), (2) saltatory (or rabbit) illusion, i.e., illusory sweeping movement of discrete taps that occur by activating actuators in sequence (Geldard and Sherrick, 1972; Lederman and Klatzky, 2009), and (3) the tendons vibration illusion, which is an illusory perception of movement that can be evoked by triggering the muscle spindle afferents through vibrations applied to the tendon (Goodwin et al., 1972; Taylor et al., 2017).

Applications for Enhancing Sensorimotor Performance and Learning

In healthy individuals, vibrotactile feedback is used to enhance motor control and learning (Lieberman and Breazeal, 2007; Van Breda et al., 2017; Shah et al., 2018). It has been demonstrated that state feedback regarding the force exerted improved the accuracy of force repetition (Ahmaniemi, ). Other studies used state and/or error feedback to guide upper limb reaching movements in the absence of visual information (Krueger et al., 2017; Shah et al., 2018; Risi et al., 2019) and to reach accuracy levels beyond the limits of natural proprioception (Risi et al., 2019). Results from a meta-analysis indicated that vibrotactile feedback was effective in reducing task completion times, but neither forces nor errors were significantly reduced (Nitsch and Färber, 2012). In addition, vibration feedback encoding center of mass or center of pressure motion was used to improve standing balance (Lee et al., 2012; Ma and Lee, 2017; Ballardini et al., ) and walking patterns (Janssen et al., 2009; Muijzer-Witteveen et al., 2017; Xu et al., 2017). Vibrotactile feedback based on stochastic resonance was applied for improving visuomotor temporal integration in hand control (Nobusako et al., 2019) and balance control (Magalhães and Kohn, 2011). Vibrations that informed the users about collisions with virtual objects in a virtual reality context added realism and improved performance (Galambos, 2012; Kaul and Rohs, 2017). Also, a vibrotactile glove interface has been used to convey sensations of virtual objects (Muramatsu et al., 2012).

Applications in Rehabilitation

In persons with multiple sclerosis, vibrotactile feedback applied to the fingernails of the contralateral hand improved the performance of a grasping and lifting task of the more impaired hand (Jiang et al., 2009). In addition, real time state vibrotactile cues reduced postural sway during standing balance tasks and improved gait parameters after stroke (Yasuda et al., 2017; Afzal et al., ), in people with Parkinson's disease (Nanhoe-Mahabier et al., 2012; High et al., 2018; Lee et al., 2018; Fino and Mancini, ) and with vestibular disorders (Sienko et al., 2012, 2013). However, in all of these studies improvements were observed during trials, and long-term effects were not tested. Vibrotactile stimulations were also used to enhance interaction realism in a rehabilitation system based on virtual reality (Boian et al., ; Dimbwadyo-Terrer et al., ), and to avoid collisions during walking in stroke survivors (Jaffe et al., 2004).

Several randomized controlled trials (RCTs) with small cohorts tested the effect of balance training programs with vibrotactile stimulations. Following a 2-week training program using vibrotactile feedback, individuals with Parkinson's disease improved their balance control parameters and performance-based measures and retained improvements 3 months after training (Rossi-Izquierdo et al., 2013). Additionally, adults with vestibular disorders improved their balance performance and felt more confident regarding their balance while performing daily activities after a training protocol with vibrotactile stimulations compared with a control group that trained without stimulations (Brugnera et al., ; Bao et al., ). Furthermore, balance improvements were retained at 6-month follow-up assessments (Bao et al., ). Also, reduced body sway and improved clinical outcome measures [e.g., Sensory Organization Test (SOT) (Franchignoni et al., ) and Dizziness Handicap Inventory (Jacobson and Newman, 1990)] were observed in a study with a large cohort of participants with vestibular disorders (n = 105) who trained with vibrotactile stimulations over 2-weeks (i.e., ten-sessions) compared with a control group that trained with a sham device (Basta et al., ).

Subthreshold vibrotactile stimulation improved somatosensation and motor function in persons with sensorimotor impairments: stimulations applied at the wrist and dorsal hand improved the immediate fingertips light-touch sensation and grip ability of the paretic hand in stroke survivors (Enders et al., ). In addition, the vibrotactile detection threshold (i.e., the minimum level of vibration amplitude to be detected) at the tip of the middle finger in persons with diabetic neuropathy and stroke survivors was decreased (Liu et al., 2002). In persons with diabetic neuropathy the threshold was decreased at the foot as well (Liu et al., 2002; Khaodhiar et al., 2003). In a pilot randomized controlled trial, subthreshold vibratory stimulation was applied to the paretic wrist of stroke survivors during upper extremity task training (a total of 6 sessions provided in 2 weeks). The treatment group showed a significant improvement in hand motor function at the end of therapy, which was sustained 19 days after therapy, whereas the control group that practiced without stimulation did not improve from baseline performance (Seo et al., 2019).

While these studies were conducted in laboratory settings, few studies provided participants with vibrotactile devices to practice at home. Bao et al. () tested the effect of long-term home-based balance training with vibrotactile sensory augmentation among community-dwelling healthy older adults. Participants were trained in static and dynamic standing and gait exercises for 8 weeks (3 sessions per week, 45-min each) using smartphone balance trainers that provided guidance while monitoring trunk sway. The experimental group received directional vibrotactile cues via actuators that were aligned around the torso in case the activation signal exceeded a pre-set threshold, while the control group practiced without supplemental feedback. Participants in the experimental group demonstrated significantly higher improvements in their SOT (Franchignoni et al., ) and Mini Balance Evaluation Systems Test scores (Clendaniel, ) compared with the control group at post training assessment. Seim et al. (2020a) designed a glove that provides subthreshold vibrotactile stimulation for stroke survivors to use at home and demonstrated the feasibility of wearing the glove for 3 h daily for 8 weeks. Also, in a double-blind RCT, chronic stroke survivors with impaired tactile sensation in the hand were given a glove to take home and asked to wear it during their normal daily routine (i.e., 3 h daily for 8 weeks) (Seim et al., 2020b). One group received a glove which provided vibrotactile stimulation to the hand and another group received a glove with the vibration disabled. Participants receiving tactile stimulations demonstrated significant improvement in tactile perception (assessed with monofilaments) in the affected hand. In another study, improvement in hand sensation was observed in participants with spinal cord injury after training with a glove providing vibration stimulations compared with participants who trained without stimulations (Estes et al., ). Vibration stimulations were applied during active practice sessions of playing piano in in-lab sessions (3 times a week for 30 min a session for 8 weeks) and during passive practice at home (2 h a day, 5 times a week). An illustration of a vibrotactile stimulation device is presented in Figure 1.

Figure 1

). The sensing unit is attached to an elastic belt worn around the torso to measure trunk sway. The four tactors are aligned over the anterior, posterior, and right and left sides of the torso to provide directional vibrotactile cues.

Applications for Conveying Social Tactile Cues

Gentle stroking touches resembling those of soft calming and caressing sensations are considered highly relevant in social interactions (Huisman et al., 2016). Using artificial means to convey such touches might enhance social presence in telecommunication or in virtual settings. Israr and Abnousi (2018), developed a vibrotactile device worn on the forearm that delivers stimuli which resemble caressing and calming sensations. Participants rated low frequency stimuli (<40 Hz) as pleasant sensations that feel like massaging and noted that they would be even more realistic with context. Huisman et al. (2013) developed a virtual agent setup that incorporates an augmented reality screen and a vibrotactile sleeve worn on the user's forearm. In this setup the forearm was placed under a tablet, thus allowing the user to see his/her forearm “through” the tablet. The vibrotactile stimulation combined with the visual representation of a hand touching the user created a more realistic touching illusion.

Assessment of Tactile Impairments

Vibrotactile simulation can be used for assessment applications. In clinical settings the duration of vibration sensation and the perception threshold are commonly measured using a tuning fork (Perkins et al., 2001; Alanazy et al., ). However, results regarding its reliability are variable across studies (O'Neill et al., 2006; Lai et al., 2014; Lanting et al., 2020), and, most importantly, the assessment does not quantitatively provide the degree of dysfunction and depends on the level of clinical experience (Lanting et al., 2020).

To address limitations of clinical assessments, an automated approach to quantify topesthesia (i.e., the ability to recognize the location of a tactile stimulus) was developed (Rinderknecht et al., 2015). The system consists of two wearable gloves that can apply vibrations on the hand at 24 possible locations and a touchscreen to directly indicate with the non-tested hand the precise location of perception on the tested hand. The assessment provides a standardized, repeatable measurement as well as continuous outcome measures on ratio scales (Rinderknecht et al., 2015). It was tested on healthy individuals (Rinderknecht et al., 2015) and on stroke survivors (Rinderknecht et al., 2019).

In addition, a portable vibrotactile stimulator device was used to probe tactile function through a battery of tests assessing reaction time (“press the button when you feel the vibrotactile stimulation”), threshold detection (the weakest detectable stimulus), amplitude and frequency discrimination (discriminating between two stimuli that are simultaneously applied and discriminating between the frequency of two sequentially applied stimuli). The battery targets different mechanisms of somatosensory processing (Holden et al., 2012; Puts et al., 2013; King et al., 2018; Tommerdahl et al., 2019; Mikkelsen et al., 2020). These tests were used on healthy adults and children (Puts et al., 2013) for monitoring recovery from concussion (King et al., 2018) as well as a wide range of neurological disorders (Tommerdahl et al., 2019). There are also other specific tests that aim to independently evaluate only one of the aspects investigated by this paradigm; an overview of the tests assessing vibrotactile perception in healthy subjects can be found in Jones and Sarter (2008).

Advantages and Disadvantages

A major advantage of vibrotactile devices is that the actuators can be easily integrated into wearable devices because they are small, lightweight, low- power, and low-cost (Alahakone and Senanayake, ). On the other hand, disadvantages of vibrotactile feedback stem from the properties of the mechanoreceptors activated by vibration. First, it is difficult to accurately locate the source of the stimulations if they are placed close together, because of the propagation of the vibration (Sofia and Jones, 2013; Shah et al., 2019) and the large size of the mechanoreceptors' receptive fields (Johnson et al., 2000). Second, it is difficult to convey directional information, unless several actuators are used in a spatially and/or temporally coordinated mode (Rotella et al., 2012). Third, it has been suggested that the feedback coding of some vibrotactile devices may be less effective than of others in reducing applied forces i.e., if the vibration frequency or location varies, vibrotactile feedback may be less effective in conveying information on intensity or direction than a uniform signal that alerts the user of a required response (Nitsch and Färber, 2012). Fourth, prolonged exposure to continuous vibratory stimulation could result in an unpleasant sensation (Bark et al., ) and has been associated with long-term nerve and tissue damage (Takeuchi et al., 1986). Also, choosing the right type, number, and target location of the actuators for patients with possible degradation of perception due to aging or disease might be challenging (Jones and Sarter, 2008).

Skin Deformation

Tangential Force and Skin Stretch

Tangential skin deformation is evoked by pressure of the skin against a device, combined with a lateral movement of the entire device or a small part of it. Such deformation occurs naturally when touched by a therapist, when interacting with a real object, or when a device applies forces on a user, but it may also be elicited by technological solutions specifically designed to provide tactile stimulation (Bark et al., ; Quek et al., 2014b; Pan et al., 2017). The stimulation is detected by the Ruffini corpuscles which are slow adapting SA-II tactile afferents in the skin that are sensitive to tangential shear strain as well as the Meissner's corpuscles which are rapid adapting RA-I tactile afferents that are sensitive to dynamic skin deformation (Johansson and Flanagan, 2009). The detection resolution of the skin stretch at the fingertip is 0.1–0.2 mm, while the direction of the stretch can be accurately perceived with less than 1.0 mm of movement (Gould et al., 1979; Greenspan and Bolanowski, 1996).