Although an increased effort has been placed on the recovery process of patients following a stroke, with recent advances in technology for monitoring the brain functions, lack of human resources in therapeutic training of patients implies that patients generally may not reach their full recovery potential when discharged from hospital following initial rehabilitation (Loureiro and Harwin, 2007). Neurological illness often manifests in clinical condition resulting in weakness of the muscles controlling the elbow and rehabilitation devices are used in order to help in recovery of muscular power (Maciejasz et al., 2014). In stroke patients, damage to the motor-, and somato-sensory cortices, makes it difficult to control and move the arm, forearm, and fingers. These patients often use assistive devices and therapy to encourage them to use their damaged limb so that the re-growth of a neural circuitry can take place that would eventually aid recovery through neuro-plasticity (Jack et al., 2001). Therefore, there is a growing interest in using robotic devices to deliver effective assistance. The aim of the robotic assistance is to provide a set of intensive and repetitive therapies to enhance the motor recovery of patients, decreasing the amount of work of a therapist. It has been found that it is important for a patient to undergo continuous exercise for successful rehabilitation (Heo et al., 2012) which robots are able to provide.

Typically, rehabilitation methods are either highly human intensive or involve attachment of rigid robotic system controlling the upper limb. Robot-based rehabilitation has been shown to have positive effects by reducing impairment (Loureiro et al., 2014). Robots provide an acceptable performance measurement test and control of the amount of exercise delivered to the subject (Kutner et al., 2014). Hard robotic structures are often based on joints connected by rigid links; this makes them heavy, with expensive and complicated control. In addition, these robotic systems are less compliant than the joints they actuate making it difficult to be directly attached to the human body unless through the use of specialized end effectors (Krebs et al., 2000), thereby mitigating their use for personal use by patients. To overcome these challenges, safe human robotic interactions, and inexpensive design can be achieved through a soft wearable robotic device (Tondu and Lopez, 2000; Tsagarakis and Caldwell, 2000).

A novel approach to rehabilitation is making use of inexpensive and soft actuators. Soft actuators are usually actuated with compressed air or SMAs (Shape Memory Alloy) (Chiu et al., 2013). SMA actuation is accomplished by embedding the trained alloy into the silicone rubber and using electric current to produce heat to deform the robot to the trained shape. Soft robots can be realized with the use of McKibben artificial muscles to produce a compliant motion similar to the skeletal muscle (Tsagarakis and Caldwell, 2000) and are actuated using a pneumatic source (Takagi et al., 2009).

Another novel approach uses embedded pneumatic networks of channels in elastomers (Ilievski et al., 2011) to achieve bending and crawling motions (Ilievski et al., 2011). Soft rehabilitation robots have been developed to generate assistive force for grasping (Shepherd et al., 2011) and gait rehabilitation (Shepherd et al., 2011). They make use of air channels embedded in elastomers to perform bending motions similar to the motion of the fingers. Other robots composed of silicone rubber for angular displacement (Sun et al., 2013) and as a 2D (Marchese et al., 2014) or 3D (Martinez et al., 2013) manipulators have been developed. An upper limb orthosis called Orthojacket actuated by pneumatics and designed for elbow rehabilitation has been developed (Schulz et al., 2011).

There have been a lot of research in developing and implementation of robotic devices for upper limb rehabilitation especially index and finger rehabilitation in the form of exoskeletons (Chiri et al., 2012; Maciejasz et al., 2014). These hand exoskeletons make use of cables (Dovat et al., 2008) and rubber (Polygerinos et al., 2015) for actuation purposes. Virtual reality has been used together with these hand exoskeletons to further aid in recovery (Ueki et al., 2012). Target tracking have also been incorporated in order to increase motivation and co-operation from the user as well as individualize exercise difficulty depending on strength the user (Jack et al., 2001).

In traditional, robotic rehabilitation systems interacting with the patient using a single distal attachment point on the forearm by means of an orthosis [for example, MIT-MANUS (Krebs et al., 2004)], exercises are defined in the XYZ Cartesian space relative to the robots single end-effector attachment point, and the assistance magnitude is modulated using impedance/admittance control schemes in the robot task-space. To support comfortably upper limb flexion and extension, WREX, Wilmington Robotic EXoskeleton, was designed at A. I. DuPont Hospital for Children to provide assistance for the wide range of natural motion in daily settings (Sanchez et al., 2006; Tariq Rahman et al., 2006). The JAECO WREX is a light weight exoskeleton with two links and four degrees of motion that approximates normal human anatomy. It incorporates elastic band elevation assists for both the shoulder and elbow to eliminate influence of gravity on the extremity (Sanchez et al., 2006; Tariq Rahman et al., 2006). The unique design of the shoulder and elbow joints allows for a significant improvement in the available range of motion when compared to other assistive devices.

A new type of wearable robots called soft exoskeletons or exosuits is becoming more popular, aiming at therapeutic intervention of upper limb by mirroring the motion of the other limb (Panasonic, 2005). Removing the external metal frame, soft exoskeletons become compliant, much lighter, and could be significantly less expensive than rigid frame wearable robots. However, soft exoskeleton's main drawback is the same as their main strength: they have no external rigid frame to support the body parts and transfer force effectively from actuator to some area of the body. We think that the effective transfer of the force should take into account the anatomical structure of limbs and joints, requiring the solid structure of the assistive device in order not to add unnecessary strain on the body parts that might damage patient joints, muscles, or tendons.

As a unique approach to a lightweight and flexible robotic structure, inflatable structures have been developed for the robotic arm as an attractive alternative method of imbuing robots with the desired lightness. Kim et al. developed the robotic arm that comprised of the inflatable links, air bag actuators, and ABS joint structures (Kim et al., 2015). Also, the novel control schemes have been applied on the basis of visual feedback control, which do not require the precise inverse kinematics for the position control (Nishida and Kawamura, 2012).

In our study, aiming at the reaching motion of the upper limb, we developed and validated the Exoskeleton Actuated by Soft Modules (EASoftM) to fulfill the four conditions; (1) A few degrees of freedom, (2) Precise motion control, (3) Wearable assistive robots, (4) Compliant assistance. We proposed the exoskeleton aligned with the anatomical structure, actuated by the soft modules located at the joint position, and the soft actuators realize the compliant motion based on pneumatic actuation and visco-elastic properties of soft materials such as plastic and rubber.

From the patient perspective, the ultra-light EASoftM offers upper limb assistance, i.e., it can assist the reaching motion of the upper limb, supporting the movement of the elbow and shoulder, and can record trajectories of hand reaching a target based on the visual feedback control. It also has high compliance and high safety integrity from the perspective of the patient, because it is entirely composed of rubber and soft modules, and attached to the body via Velcro straps. We first describe the design specification of the EASoftM with the scene setting (Sections 2.1 and 2.2), and secondly describe the detailed kinematics and the vision-based control schemes (Sections 3.1–3.3). After explaining the production of the plastic modules (Section 3.4), their torque characteristics and reliability were presented (Section 4). In the Result section (Section 5.1), a series of experiments is described for the motion of one and two degrees of freedom, first tested by using the weight. Finally, we presented the participant experiments, demonstrating the closed-loop reaching motion on precise position control (Section 5.2). The General discussion is given in Section 6.

As a contribution to neurorehabilitation, the EASoftM can be integrated with the Brain Computer Interface, for example, for detecting the motor command generation by online electroencephalogram (EEG) analysis, in order for the EASoftM to guide the hand to a target position in a rehabilitation therapy. The advantage of using EASoftM is that it does not include any motors which generate the elecro-magnetic waves which inevitably influence the electric signals from brain activity.

Fulfilling the design specifications in the Section 2.2 in order to assist comfortable flexion and extension of the upper limb, we mainly concentrated on three characteristics; (1) A few degrees of freedom; anatomically structured exoskeleton with the parallel links for gravity compensation, (2) Compliant assistance: soft modules to actuate the elbow and shoulder joints, and (3) Precise motion control: visual control loop to guide the hand to the target at high precision.

The torque characteristics of soft actuators, torque as a function of the joint angle, was investigated using the experimental setup shown in Figure 5. We performed the torque measurement of the soft modules in the following procedure;

Thus, in Figures 6, 7 we measured the torque produced by the soft module at the equilibrium state by fixing the angle of the joint in Figure 5. We characterized the functional properties of the soft modules. The torque was measured as a function of (1) pressure in the range from −30 to 30 [kPa] at the incremental step of 3.0 [kPa]; and (2) an angle when the soft module was actuating the rotational joint with two rigid arms (Figure 5).

Figure 6 shows the torque as a function of (a) Pressure and (b) Joint angle. The general trend can be observed; (1) the torque increased as a function of pressure and (2) the torque decreased as a function of angle. For the case of applying the negative pressure to the soft module, Figure 7 shows the torque as a function of (a) Pressure and (b) Joint angle. The general trend can be noted; (1) the torque increased as a function of pressure and (2) the torque increased as a function of an angle.

We expect that the largest hysteresis when switching the pressure from positive to negative, as it takes a certain time for the air flow in pipes and plastic modules to relax to the steady state. However, we aim at the upper limb assistance in slow motion, thus, air flow would be equilibrated throughout the actuation.

The developed Exoskeleton Actuated by Soft Modules is shown in Figure 8. The rubber bands were attached to the parallel structures of the exoskeleton in order to compensate the gravity, and the soft modules were attached in-between two plastic plates on shoulder and elbow joints. The total weight of the EASoftM was 967 [g], composed of assembled 3D printed arm (724 [g]), soft module (31 [g]), and attachment (181 [g]). The end-effector was attached to the end-point of the links, and the camera was located on the shoulder position to apply the visual feedback control in Figure 1.

In the following sections, we validated the functional properties of the EASoftM, first by putting the weight of 1.0 [kg] on the attachment of the exoskeleton arm, and secondly, by performing the participant experiments as shown in Figure 8D. In both experiments, the relative distance between the end-effector and target, and trajectories in the 2D camera frames were measured as a function of time as well as the pressure applied to the individual soft modules.

Therapeutic intervention using the assistive robots has been proven to be effective when including the following design specification (Loureiro et al., 2014);

To realize the precise motion with a few degrees of freedom, the conventional methods would suggest the industrial type robot such as metal exoskeleton which is a hard, rigid structure and heavy (Krebs et al., 2000), not fulfilling the condition 3. A new type of a wearable robot called soft exoskeletons or exosuits is an interesting alternative. Removing the external metal frame, soft exoskeletons become compliant, much lighter, and could be significantly less expensive than rigid frame wearable robots (Panasonic, 2005). However, soft exoskeletons main drawback is the same as their main strength: they have no external rigid frame to support the body parts and transfer force effectively from actuator to some area of body.

We think that the effective transfer of the force should take into account the anatomical structure of limbs and joints, requiring the solid structure of the assistive device. Elderly and disabled people already have weakened bones and muscles, so if the force is transmitted in the wrong manner, adding unnecessary strain to their body parts, it might lead to joint degeneration, damage their muscles or tendons. Thus, in our study, aiming at the reaching motion of upper limb, we developed and validated the exoskeleton actuated by soft modules to fulfill these four conditions. We proposed the exoskeleton aligned with the anatomical structure actuated by the soft modules located at the joint positions, and these soft actuators realized the compliant motion based on pneumatic actuation and visco-elastic properties of soft materials such as plastic and rubber. As far as we are aware of, this proposed structure demonstrated the first possibility of integrating the rigid exoskeleton and the soft actuators to assist the reaching motion, as well as the vision-based control law showing its effective functionality in guiding the hand of the participant to the target.

This vision-based control has a certain advantage when the exoskeleton is used in the daily life, i.e. the visual analysis can be easily extended to detect the target such as cups and pens in the work space, and it does not require any encoders and a set of cables transmitting the signals, which add technical complexity to the integrated system. Thus, closing the control loop only by visual information is a flexible solution that can easily integrate low level motion control with higher level intelligent control. More specifically, since we aim at slow reaching motion, the necessary torque mainly will be used to compensate the gravity. Although, it is in principle possible to use the active actuator for this purpose, however, it would be hard to produce the wearable device aligned with the anatomical structure, as it would increase the number of actuators required. Thus, in our study we used the passive actuator for gravity compensation to decrease the weight for wearable purposes. As a next step, we developed the pneumatic actuators made of plastic sheets, which has good tensile strength and is light, and could produce substantial torque for our purposes under 1 atmospheric pressure. Conventionally, antagonist actuator is necessary to actuate the single joint, resulting in more weight and higher number of tubes. In our study, we could successfully demonstrate that the positive and negative pressure can be applied subsequently to produce the torque to increase and decrease the angle of joints. The low pressure actuation contributed to the smooth transition of the pressure as shown in Figures 6, 7.

Most of the assistive robots were made of rigid links and motors which used metallic materials. To realize the compliant motion, the mechanical structure required additional component such as spring, which also added more weight onto the whole structure (Loureiro et al., 2011). Also, considering the assistive soft robotics, though the pneumatic actuators are light weighted, they were used with the metal links and pulleys, thus, the total weight tend to increase, making them inappropriate for the wearable solution (for example, see Schulz et al., 2011). Our proposed exoskeleton aimed at the ultra-light solution, using the 3D printed links and the soft modules (plastic sheets) for actuation, and reducing the number of actuations by employing the negative pressure actuation and gravity compensation. In addition, despite of the challenges imposed by such choice of hardware components materials, we did not lose the precision of position control since the vision-based control was employed.

The further work is planned to make a whole system portable and wearable. This can be achieved by the pneumatic actuators, the regulators and the power supplies being mounted in a waist belt pack so that the participants can freely move around. Also, aiming at the wearable and portable system, we can use the small motors to pump in the air, and the simple electric circuits to control the pressure of the soft modules (Oguntosin et al., 2015). By placing those electric components in the waist belt, the electromagnetic waves should not interfere with the EEG measurement. In the near future, we will integrate the robotic system with an eye tracking system to transmit the intention of the participant identifying the desired targets, as a natural extension of the vision-based control schemes toward the daily exercise. As a mid-term plan, we will integrate the proposed robotic system with Brain Computer Interface to estimate the user's motion intention in order to trigger the assistive motion (Hayashi et al., 2012; Kondo et al., 2015), as the system discussed in this article provides an optimal solution for the measurement of the EEG signals, since its construction made of plastic (metal-free structure and actuation) in principle does not produce any electromagnetic waves.

This study was carried out in accordance with the recommendations of Ritsumeikan medical ethical guidelines and Ritsumeikan Ethical Committee with written informed consent from all subjects (BKC-medical-2016-051). All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ritsumeikan Ethical Committee.

VO and YM substantially contributed to the development of the systems, data acquisition, and analysis. HK contributed to the performance of experiments, and the interpretation of the results. SN, SK, and YH contributed to the design of the work and overall discussion. All of us contributed to the writing of the paper.