IEEE ROBOTICS AND AUTOMATION LETTERS, VOL. 4, NO. 3, JULY 2019 2547

A Soft Wearable Robotic Ankle-Foot-Orthosisfor Post-Stroke Patients

Junghan Kwon , Ji-Hong Park, Subyeong Ku, YeongHyeon Jeong, Nam-Jong Paik , and Yong-Lae Park

Abstract—We propose a soft robotic ankle-foot-orthosis for post-stroke patients, which is inexpensive, lightweight, easy to wear, andcapable of gait assistance for rehabilitation not only in the clinic butalso in daily life. The device includes a 3D-printed flexible braceand an ankle supportthat allows natural flexion and extension ofthe ankle but provides support in the vertical direction prevent-ing the structure from buckling. A bi-directional tendon-drivenactuator was used for assisting both dorsiflexion and plantarflex-ion. The device also contains a wearable gait sensing module formeasuring the leg trajectory and the foot pressures in real time forfeedback control. Since the device is powered by a rechargeablebattery and communicates with the main controller wirelessly, itis fully untethered, making it mobile and comfortable. Using themeasured sensor data and the biomechanics of the legs, the real-time gait phase is detected, and then a gait assistance algorithmfor both dorsiflexion and plantarflexion provides an accurate pre-diction of a control phase and timing although there are variationsin the gait trajectories among individuals. As a feasibility test, thewalking experiment was conducted with a post-stroke patient. Theresult showed improvement in both gait propulsion and foot-dropprevention.

Index Terms—Soft robotics, wearable robotics, post-stroke re-habilitation, gait detection.

I. INTRODUCTION

WALKING is a repeated sequence of motions by mov-ing two legs alternately, and it is one of the most

Manuscript received October 15, 2018; accepted March 10, 2019. Date ofpublication April 1, 2019; date of current version April 12, 2019. This letter wasrecommended for publication by Associate Editor C.-H. Yeow and Editor K.-J.Cho upon evaluation of the reviewers’ comments. This work was supported inpart by the National Research Foundation of Korea funded by the Korean Gov-ernment (MSIT) under Grant NRF-2016R1A5A1938472, in part by the SeoulNational University Bundang Hospital Research Fund under Grant 14-2017-025,and in part by the Interdisciplinary Research Initiatives Program under Grant800-20170165 from College of Engineering and College of Medicine, SeoulNational University. (Junghan Kwon and Ji-Hong Park contributed equally tothis work.) (Corresponding authors: Nam-Jong Paik; Yong-Lae Park.)

J. Kwon, S. Ku, Y. Jeong, and Y.-L. Park are with the Departmentof Mechanical and Aerospace Engineering, Soft Robotics Research Cen-ter, Institute of Advanced Machines and Design, Seoul National University,Seoul 08826, South Korea (e-mail:, jhkwon@snu.ac.kr; shetshield@snu.ac.kr;yunghyun1208@snu.ac.kr; ylpark@snu.ac.kr).

J.-H. Park and N.-J. Paik are with the Seoul National University BundangHospital, Seongnam 13620, South Korea (e-mail:,parkjihong.md@gmail.com;njpaik@snubh.org).

This letter has supplementary downloadable material available athttp://ieeexplore.ieee.org, provided by the authors. This video, viewable withQuickTime Player (MAC), VLC Media Player (Windows), shows the design,fabrication, control of Soft Wearable Robotic Orthosis for rehabilitation of post-stroke patients. The size of the video is 6.55 MB. Contact (jhkwon@snu.ac.kr)for further questions about this work.

Digital Object Identifier 10.1109/LRA.2019.2908491

important functions in daily life. Since walking is performed byharmonious cooperation of bones, muscles, sensory receptors, aneurotransmission system, and central and peripheral nerve sys-tems, gait disorders can occur if there is a disease in one of thesesubsystems [1]–[3]. Particularly, post-stroke patients accompa-nied by hemiplegia experience muscular weakness of their anklejoints, which induces degradation of propulsion force during thestance phase and reduced clearance during the swing phase dueto foot-drop. This muscular weakness increases the degree ofasymmetry in leg movements, muscle fatigues, and the risk offalls during walking. Even if the patient does not die due to thisdisorder, a long-term treatment is necessary causing physical,economical, and mental costs.

Currently, various types of assistive devices are used for gaitrehabilitation. A plastic ankle-foot orthosis (AFO) is the mostwidely used to improve the alignment of the ankle joint, in-creasing the walking speed and reducing the energy consump-tion during walking [4]–[6]. However, since the AFO permitsonly limited ankle motions with zero degree of freedom, themovement of the ankle is significantly different from normalwalking gait pattern. Although a certain level of gait motionscan be achieved by using hinge joints and springs, this only per-mits passive movements with a predetermined stiffness and verylimited degrees of freedom.

To overcome this limitation, robotic devices with active asis-tances have been developed, and their positive clinical effectsfor gait rehabilitation have been reported [7]–[10]. However, thenumber of patients receiving treatment using a robotic device ishighly limited due to its high cost and bulkiness. Therefore, thereis a demand for a device that is inexpensive, lightweight, andeasy to wear, and can be used for gait rehabilitation in hospital,home and daily life.

To address the above issues, there are several challenges toovercome. First, an orthosis made of rigid materials can causediscomfort to the wearer and restrict the natural movement dur-ing walking. As a solution, it is possible to use flexible materialsmaking the device light and easy to wear when made in a formof clothes. For this reason, soft wearable devices [11]–[14] havebeen recently proposed. With soft materials, anchoring of theactuators and sensors on a brace should be carefully consid-ered to prevent slippage of components and pressure concen-tration on the skin. It can be designed in a form that wraps awide area of a fixed part of the body’s convex geometry, suchas hips and knees, and distributes the pressures. However, thiscan make the system bulky due to the large area of the structureeven though the device is only for a single joint. Therefore, it isnecessary to minimize the size of the orthosis while allow-ing bending motions of the ankle and preventing slippage and

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2548 IEEE ROBOTICS AND AUTOMATION LETTERS, VOL. 4, NO. 3, JULY 2019

Fig. 1. Illustration of a prototype of the soft wearable robotic ankle-foot-orthosis for post-stroke patients.

vertical force for anchoring. In addition, a simple and automatedfabrication process is required to be competitive in price.

Second, since soft actuators, such as pneumatic artificial mus-cles (PAMs) [15], [16] and tendon-driven systems [17]–[19]produce only pulling forces, an antagonistic pair of actuatorsare required to assist both dorsiflexion and plantarflexioin mo-tions. However, the system in this case may be more complexand heavier as the number of actuators increases. To address thisissue, a cable-pulling mechanism in both directions with a singlemotor has been introduced [18].

Third, a gait sensing module and a detection algorithm arerequired to control the actuator of the orthosis at proper timing. Inparticular, post-stroke patients have different gait patterns fromthose of normal people, and individual differences also exist.Since it is difficult to estimate the walking state and the controltiming with a limited number of sensors, individual tuning ofcontrol parameters has been introduced [12].

For these reasons, we propose a soft wearable robotic ankle-foot orthosis with a bi-directional tendon-driven actuator forpost-stroke patients (Fig. 1). We also present a fabricationmethod taking advantage of 3D printing of flexible materials.

The proposed brace was designed with two flexible columnsthat allow natural flexion motions of the ankle joint while pro-viding vertical supports preventing the structure from buckling.Wearable gait sensing modules were also developed to measurethe wearer’s lower limb motions and foot-ground contacts, andintegrated with the actuation module and the real-time controlsystem. From the sensor data, a skeletal model of the legs wasconstructed in a sagittal plane, and the gait phase was detected inreal-time with the accurate prediction of a control phase and tim-ing although there are differences in the gait trajectories amongindividuals. Then, the assistive force was generated for bothdorsiflexion and plantarflexion.

To evaluate the performance of the device, a test of groundwalking was carried out with a post-stroke patient. The ex-perimental results showed improvement in gait propulsion andfoot-drop prevention by the proposed control algorithm whichsuccessfully estimated the control timing in real time.

Fig. 2. Design and prototyping of flexible ankle brace. (a) 3D printing of flexi-ble filament. (b) Flexible but incompressible ankle column. (c) Actual prototypewith ankle mock-up. (d) Simple wearing process using Velcro straps.

The rest of this letter is organized as follows. Section II de-scribes the design of the soft robotic orthosis, followed by thestrategy of gait phase detection and assistive-force-generationalgorithm in Section III. The experimental results of a feasibil-ity test of ground walking with/without the device are presentedin Section IV, and Section V concludes the letter.

II. DESIGN

A. Flexible Ankle Brace

The ankle brace was fabricated using a 3D-printer (CubiconSingle Plus, Cubicon Inc.) (Fig. 2-a), which enabled quick fabri-cation and easy parameter changes in the orthosis design accord-ing to the body size of the user. To improve the wearability ofthe brace, a flexible thermoplastic polyurethane filament (TPU,Cubicon Inc.) was used as a 3D-printing material. The selectedTPU material shows similar flexibility to leather when printed inthin sheets while providing relatively high stiffness in the formof columns or blocks.

The brace was also designed to effectively anchor the actuatorfor driving tendons (Fig. 2-b). Two flexible columns connectingthe shank and the heel pads allow rotation of the ankle while pre-venting vertical compression (i.e., buckling). This is necessaryfor anchoring that prevents the shank pad from slipping evenwhen the brace is loosely tied to the shank, only transmitting theassistive torque to the ankle for rotation.

The proposed brace is an open-toe design, and adjustment canbe easily made to fit the foot size using a Velcro strap to achieveboth robust anchoring and easy wear-and-removal, as shown inFig. 2-c and 2-d. The foot size available for this prototype isabout 240 mm to 280 mm.

KWON et al.: SOFT WEARABLE ROBOTIC ANKLE-FOOT-ORTHOSIS FOR POST-STROKE PATIENTS 2549

Fig. 3. Bi-directional tendon-driven actuation module. (a) Components.Cable-pulling mechanisms for (b) plantarflexion and (c) dorsiflexion.

The orthosis is 330 mm tall, 160 mm wide, and the total weightof the device is 1,540 g including the flexible ankle brace withthe actuation module (580 g), the sensing module (400 g), andthe controller with a battery (560 g).

B. Actuation Module

A bi-directional tendon-driven winch module with an electricmotor was developed to minimize the size and the weight ofthe device, as shown in Fig. 3. The pulley and the housing partswere made of a rigid plastic material (VeroBlack Plus, Stratasys)using a polyjet 3d-printer (Object30 Prime, Stratasys), with twoBowden cables wound together on one pulley to produce pullingforces for both plantarflexion and dorsiflexion (Fig. 3-b and3-c). This actuation module was attached on the shank pad ofthe flexible ankle brace to reduce the distance of cable routingand the friction in the cables. A commercial high-performanceelectric motor integrated with gears and a rotary encoder (MX-64T, ROBOTIS) was employed to achieve a pulling force and astroke of up to 70 N and 100 mm, respectively with the pulley.In this study, the maximum assistive force of 70 N was targetedin plantarflexion.

For motor control, a current-based torque controller was em-ployed to directly generate desired pulling forces. This controlapproach reinforces safety in human-robot interactions becauseit maintains the same output force upon a given command inputdespite sudden position changes in gait that may occur due tounexpected disturbances.

C. Gait Sensing Module

A soft wearable gait sensing module was also developed formeasuring the motions of both legs and the ground reactionforces (GRFs) of both feet in real-time (Fig. 4-a). Soft strainsensors were attached on the knee and the ankle joints to mea-sure relative joint angles, θk and θa, respectively. The designof the soft sensors was based on our previous work [20], [21].An inertial measurement unit (IMU) (MW-AHRS, NTRexLAB)was additionally attached to each shank to measure the absolutejoint angles of the shank θs with respect to the ground. Then,the hip joint ankle was calculated from the measured knee ankleθk and the shank angle θs. The length of the thigh lt, shanklt,

Fig. 4. Soft wearable gait sensing module: (a) components of the module.(b) model of the human leg in a sagittal plane. (c) a photo wearing the sensingmodules on both legs and a soft orthosis on the right leg.

and foot lf segment were measured from the wearer in advance.Using the measured data from the soft strain sensors and theIMUs, a kinematic model of the human legs in the sagittal planewas constructed, as shown in Fig. 4-b. An insole with three forcesensitive resistors (FSRs) (Flex force, Tekscan) was also used todetect the ground contact of each foot.

The sensor data were collected by a microcontroller (ArduinoMKR-1000) operated remotely and powered by a battery. Thewireless communication between the sensor board and the maincontroller allowed the entire brace to be fully untethered andcomfortable during walking (Fig. 4-c).

D. Control Hardware

The remote main controller communicates wirelessly with alocal motor controller that was worn by the user (Fig. 5). Uponreceiving the command signals, the portable motor, powered bya 12 V rechargeable battery pack, generates a torque input to

2550 IEEE ROBOTICS AND AUTOMATION LETTERS, VOL. 4, NO. 3, JULY 2019

Fig. 5. Configuration of the control hardware interface.

Fig. 6. Screenshot of graphic user interface for monitoring and recording.

the winch that drives the ankle of the wearer. The main con-troller receives sensor data from the sensing module, recognizesthe current walking pattern, calculates the appropriate controlforce, and transmits the command to the motor controller. Agraphical user interface (GUI) in the main controller addition-ally lets the user monitor and log the current walking status(Fig. 6). This data can be used not only for real-time feedbackcontrol of the robotic orthosis but also for providing quantitativeinformation of the patient’s gait patterns to caregivers or clinicalstaffs.

III. GAIT DETECTION AND CONTROL

A. Real-Time Gait Phase Detection Algorithm

The gait phase of the patient is detected in real-time basedon the measured foot-ground contact information and the gaitmotion of the paretic side on the sagittal plane (Fig. 7-a).

In a previous study, the sensor data were measured by a gyrosensor on foot, and the gait event of the current gait cycle waspredicted from the sensor data of the last three gait cycles [13].This method works if the walking speed and the pattern arerelatively constant, but the accuracy may become lowered ifthey change suddenly. This is due to the difference of the gaitpatterns in the previous and the current gait cycles.

Fig. 7. Gait detection and control strategy: (a)the kinematic leg model recre-ated for each instance in frames below it for a gait cycle. (b) FSR signals offoot pressure insole. (c) Estimated GRF angle. (d) control strategy for three gaitphases.

However, the posture of the leg was directly calculated in realtime in our algorithm based on the soft sensor data and the IMUsattached to the both legs and the kinematic model of the legs.This approach always uses the sensor data at each moment inthe current gait cycle, and hence, it responds quickly to changesin the gait speed and the patterns.

We distinguished the stance and the the swing phases usingthe foot-ground contact information (Fig. 7-b). The stance wasdetermined by the period from heel strike until toe-off.

The heel rise event was determined based on the direction ofthe GRF (Fig. 7-c). After calculating the positions of the ankleand the hip joints from the sketch model of the lower limb, weassumed that the direction of the GRF was in the same directionof the vector from the ankle joint to hip joint (Fig. 4-b). Then, theheel rise event was determined when the direction of the GRFwas perpendicular to the ground.

This assumption makes the center of pressure (COP) fixedat the ankle joint and does not include the COP movement ofapproximately±10 cm during the stance phase. By assuming the

KWON et al.: SOFT WEARABLE ROBOTIC ANKLE-FOOT-ORTHOSIS FOR POST-STROKE PATIENTS 2551

leg length of 80 cm, the maximum error for this approximationwas calculated as ±7.1◦. The error would be relatively large inthe toe-off events due to the difference between the position ofthe actual COP and the ankle joint. On the other hand, duringthe heel strike and the heel rise events, the errors were reducedbecause the position of the COP was close to the ankle position.Since we used the estimated GRF direction to find the heel riseevent, this approximation would be applicable.

B. Assistive Force Generation

Assistive force was generated from the results of the gait phaseand the gait events detection. The peak plantarflexion momentacting on the ankle during normal walking was considered as1.31 Nm/kg on average [22]. Assuming the length of the momentarm from the center of the ankle to the cable is 8 cm and thepatient’s weight is 65 kg, this moment corresponds to a pullingforce of 1,064 N. In this study, the maximum assistive forceof 70 N was generated in plantarflexion, which corresponds toapproximately 6.6%.

The control command was divided into three stages(Fig. 7-d). First, between the heel strike event and the heel riseevent, a pulling force of 30 N in the plantarflexion directionwas generated to remove the cable slick. Second, between theheel rise event and the toe-off event, a larger pulling force of70 N was generated in the plantarflexion direction to assist thewearer’s walking. Finally, between the toe-off event and the nextheel strike, a pulling force of 50 N in the dorsiflexion directionwas generated for prevention of foot-drop.

Our algorithm does not estimate the gait event using the pre-vious gait cycles but estimates the gait event at each moment ofthe gait cycle in real-time, and the method for finding the heelrise event from the change of the estimated GRF direction wasimplemented. Using this heel rise timing as a starting point forassisting plantarflexion, control timing can be generated withouttuning parameters individually.

IV. RESULTS

A. Experimental Setup and Protocol

A feasibility test of ground walking was carried out to eval-uate the performance of the prototype of the soft wearablerobotic orthosis with a 49-year-old male chronic stroke patient infunctional ambulation category 3. He had right middle cerebralartery infarction 10 months before the experiment. His Fugl-Meyer assessment lower extremity score was 24 out of 34 onthe paretic side, and his performance on 10-meter walking testwas 16.35 seconds. He underwent 3-D gait analysis which wasperformed using an optical motion capture system (Vicon 370,VICON) and a force plate (Kistler) (Fig. 8). An experiencedoperator placed 15 reflective markers to calculate the kinematicdata [23].

The gait analysis was performed under three different walk-ing conditions: 1) without the orthosis, 2) wearing the orthosiswithout actuation, and 3) wearing the orthosis with actuation.Motion was captured three times on a nine-meter walkway. Theaverage kinematic data along with the spatio-temporal parame-ters, such as stride length, cadence, and walking speed were alsoobtained. The swing time asymmetry was calculated by dividing

Fig. 8. Schematic representation of experimental setup.

the largest swing time by the sum of the largest and the smallestswing times. The asymmetry was calculated in the same man-ner for the step length. The paretic propulsion was calculated asthe time integral of the positive anteroposterior ground reactionforces according to previous study [24].

The study protocol was approved by the institutional reviewboard (IRB protocol number, B-1802-451-006) of Seoul Na-tional University Bundang Hospital. The informed consent wasobtained from the participant in agreement with the rules of theEthics Committee.

B. Experimental Results

The joint angle of the paretic ankle of the subject in eachcondition was measured throughout the gait cycle (Fig. 9-a).The green line indicates the average movement of the ankle ofnormal population. Without the orthosis, the ankle joint wasmore plantar-flexed after toe-off and ended the gait cycle with-out sufficient dorsiflexion. With the orthosis unactuated, theplantarflexion and dorsiflexion were both limited compared withnormal motions. With orthosis actuated, appropriate plantarflex-ion was achieved at the proper moment during the gait cycle.The dorsiflexion showed a peak of approximately 10◦ higherwith the actuated orthosis. However, the slope was similar to thecondition without the orthosis. The amount of the assistive forcefor dorsiflexion after toe-off might not be enough for this subject.

The experimental results showed that the paretic propulsionof the subject was increased by wearing the unactuated orthosis,and further increased by the actuated orthosis (Fig. 9-b). Thus,our device would bestow stronger propulsive strength for thestroke patients with low paretic propulsion. The improvementof the swing time and the step length asymmetry was not obvi-ous (Fig. 9-c), which means that our device did not mitigate thesubject’s gait asymmetry in the spatio-temporal aspect. This alsoimplies that the abnormality of the non-paretic side in the hemi-plegic gait was not corrected. It is necessary to control the timingof plantarflexion assistance according to the patient’s walkingspeed and to consider the problems, such as the lateral shiftingof the weight during walking. Further investigation with largersamples of walking trials would be necessary.

2552 IEEE ROBOTICS AND AUTOMATION LETTERS, VOL. 4, NO. 3, JULY 2019

Fig. 9. Experimental result of preliminary clinical test. (a) Improved anklejoint angle in a gait cycle with the device on. (b) Improved foot propulsion ofparetic side. (c) Gait symmetry was also improved but not significant.

V. CONCLUSION

In this study, we developed a prototype of the robotic ankle-foot-orthosis for post-stroke patients. A soft wearable gait sens-ing module was also developed for measuring the lower limbmotion and the foot-ground contact. Then, the gait phase wasdetected in real-time based on the sensing data and biomechan-ics of the wearer’s leg motion, and finally, assistive force forboth dorsiflexion and plantarflexion was generated with accu-rate prediction of a control phase and timing.

To evaluate the performance of the prototype, a ground walk-ing test with a post-stroke patient was performed. The resultsshowed improvement in gait propulsion and foot-drop preven-tion. This suggests that the proposed orthosis and control algo-rithm have potential in the improvement of the hemiplegic gaitafter stroke.

Testing the device with only one patient is the limitation ofour study. Future plans include upgrade of the orthosis designand clinical trials with a larger number of patients.

ACKNOWLEDGMENT

The institute of Engineering Research at SNU provided theresearch facilities for this work.

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