INTRODUCTION
Although walking is the most basic form of transportation, walking disabilities affect the quality of life and the ability to move independently (Frizera-Neto et al., 2011; Pirker and Katzenschlager, 2017). Several conditions such as old age, accidents, or medical surgeries can all cause walking difficulties either temporarily or permanently. People who suffer from these conditions are advised to use walking assistive devices such as a walker, cane, or crutches, which are integral parts of their rehabilitation treatment. These orthotic walking aids help keep the weight off the injured or weak limb, assist with balance, and enable the patients to perform their daily activities more safely.
There are different types of commonly used orthotic walking aids, which vary according to size, configuration structure, contact type on the floor, and purpose of intended use (Frizera-Neto et al., 2011). Orthotic walking aids were classified into canes, crutches, walkers, and rollators (Choi et al., 2019). The choice of one of these walking aids depends on the physical disability and the level of disease of the individual and cognitive functions (Frizera-Neto et al., 2011). Inappropriate selection of aids causes a poor gait pattern and the risk of falls. The cane is one of the types of simple assistive aids made of wood or metal (Goher and Fadlallah, 2020). It is used for patients who need one upper limb to help balance, and the stick is handled by the upper limb opposite to the affected leg (Martins et al., 2012). The crutches need upper physical strength to bear the weight and are often used temporarily. Crutches are divided into forearm crutches and axillary crutches (Van Hook et al., 2003). Such walking aids require higher balance skills due to smaller bases touching the ground surface.
One of the types of walking aids that enhance stability and increase the patient’s support base is the orthotic walker, which is easier to use than other assistive aids (Van Hook et al., 2003; Martins et al., 2012). Orthotic walkers are categorized into four categories. First, standard walkers, which have four legs that must touch the ground simultaneously and require the patient’s ability to raise the aid forward to walk (Van Hook et al., 2003; Kloos et al., 2012), useful for patients with poor gait balance (Frizera Neto et al., 2010). Second, the walker with three or four front wheels (rollator), in which the wheels provide smooth and faster movement because they do not need the patient lifting the walker for movement (Kloos et al., 2012). Yet, it lacks stability, and the patient is at a higher risk of falling (Van Hook et al., 2003). Third, the reciprocal walker is designed to simulate the natural pattern of gait. It is similar to the standard walker but allows the sides to be moved alternately (Frizera-Neto et al., 2011). The fourth category is the two-wheeled walker, which combines the standard walker and the rollator walker (Frizera-Neto et al., 2011). Among the above-described orthotic walkers, reciprocal walkers gained higher acceptance due to their simplicity, cost-effectiveness, and similarity to the normal gait pattern (Bateni and Maki, 2005; Martins et al., 2012; Abualait and Alnajdi, 2021).
The gait of an individual can be described as a sequence of rhythmic, alternating movements of the trunk and limbs which results in the forward progression of the center of gravity (Martins et al., 2012). This sequence of rhythmic, alternating movements refers to the gait cycle. Therefore, any change in the gait cycle for a prolonged period exerts a negative and unintended effect on the gait (Bateni and Maki, 2005; Chan et al., 2005). Even though patients regain their walking ability, their gait abnormalities persist as patients tend to bear more weight on the healthy limb, which leads to asymmetrical weight bearing leading to asymmetrical gait (Cichy et al., 2008). To address gait asymmetry, a real-time visual feedback system is needed to aid patients in correcting their gait balance as they walk.
The objectives of this study are to design, develop, and prove the concept of an orthotic walker equipped with a real-time visual feedback system to aid patients in correcting their gait symmetry as they walk. This was done by installing a real-time visual feedback system on a traditional reciprocal orthotic walker. The visual feedback system was 3D modeled and 3D printed utilizing SolidWorks 2021 (Dassault Systèmes, France) and Original Prusa i3 MK3S+ (Prusa, Prague, Czech) 3D printer, respectively. This visual feedback system relies on load cells installed inside the tips of the orthotic walker legs, which measure the force being exerted on each side of the orthotic walker (Lancaster and Kocher, 1994; Adrezin et al., 1996; Alwan et al., 2006). The visual feedback system was tested to give the patients real-time feedback about their gait balance which may help to correct their asymmetrical weight bearing on either of their two lower limbs.
METHODS
Gait analysis
The data of the normal gait and the gait with orthotic walker support of two healthy female volunteers, aged 22 and 23 years old, were collected by a force measurement system (Footprint Center, Riyadh, Saudi Arabia). The emed® platform (Novel Electronic Incorporated, Munich, Germany) was utilized to analyze gaits with and without an orthotic walker.
Internal components
The system was designed using four 50-kg Wheatstone half-bridge strain gauge load cells, model HMD7003 (Yuyao Tongyong Meter Co., Ltd, Ningbo, Zhejiang, China) (Fig. 1). The total combined load would be up to 200 kg distributed equally (50 kg) under each leg of the orthotic walker. The HX711 amplifier model MOD-HUM-AMPM-257 (SILIRS Technologies Pvt., Ltd, Bangalore, India) was utilized to amplify the acquired signal to get measurable data out from the load cell (Fig. 2). Arduino Uno SMD R3 (Smart Project Co., Pescara, Italy) (Fig. 3) was utilized to process data acquired by load cells. A 16*2 character I2C liquid crystal display (LCD) screen model GH1602-2505 (Hunan Huayuan Display Technology Co. Ltd. and Shenzhen Huayuan Display Technique Co. Ltd., Guangdong, China) (Fig. 4) was utilized to display the collected data and combined weight on each side of the orthotic walker. The circuit connection was tested using the Wokwi simulator software.
Computer-assisted design modeling
SolidWorks 2021 was utilized to design a two-dimensional model, which was then converted into a printed 3D model for load cell housing that encompasses the load cells and facilitates the operation of the entire feedback system, and this was installed at the bottom of each leg of the orthotic walker.
Computer-assisted manufacturing modeling
The manufacturing process was done by the three-dimensional (3D) Printing Lab (King Saud University, Riyadh, KSA) using an Original Prusa i3 MK3S+ 3D printer. It utilizes the fused deposition modeling method, in which the filament is released from a heated nozzle that is positioned in three directions; the filament hardens as it leaves the nozzle and reduces in temperature to form the required structure (Bach, 2018).
The material chosen was polyethylene terephthalate glycol (PETG). PETG filament is strong compared to other materials, reaching a flexural strength of 66 ± 2 MPa, is also durable, and does not shrink or deform. The tensile yield strength is 47 ± 2 MPa, while the tensile modulus is 1.5 ± 0.1 GPa. PETG filament was a suitable choice as it has good mechanical properties and impact resistance, suitable for outdoor use. Also, it has good temperature resistance (68°C) and to some extent UV and water resistance (Bach, 2018).
Software coding
The Arduino Uno programming was done using Arduino IDE 2.0 software in C++ language. Two Arduino library were used for HX711 (HX711.h) and the I2C (LiquidCrystal_I2C.h).
Validity test
To validate that the orthotic walker measures the actual exerted weight on each side of the orthotic walker, known loads of 5, 10, 15, and 20 kg weights were utilized. Each tip, which includes the load cell, of the orthotic walker was removed from the walker and the weight was balanced on top of it, and 64 data points were recorded during 1 min.
Orthotic walker proof-of-concept
Five female volunteers tested the orthotic walker with the visual feedback system. Two females were healthy, aged 22 and 23 years old, and weighed 43 and 45 kg, respectively. The other three female volunteers were 56, 58, and 55 years old and weighed 93, 82, and 87 kg, respectively, and all three had total knee replacement (TKR) surgeries for their right knees >5 years ago and previously utilized traditional rehabilitation orthotic walkers for a month or two. All volunteers used the orthotic walker with the visual feedback system for 3 min and data were collected.
RESULTS
Gait analysis
Gait analysis was done with and without the orthotic walker to measure if there was a difference in max force applied by the right and left feet of each volunteer. The two healthy female volunteers aged 22 and 23 years old and weighs 43 kg and 45 kg respectively. Their gait analysis data were collected by a force measurement system utilizing the emed® platform.
The emed® platform is a precise electronic system that can measure and analyze the pressure distribution under the foot in both static and dynamic situations. During the study of the barefoot pressure data, foot abnormalities and malfunction can be found by using calibrated capacitive sensors, which have two sensors for every 2 cm2 with a total of 6080 sensors. Dimensions of the footprint pad are 700 × 403 × 15.5 mm3, and the pressure level ranges from 10 to 1720 kPa (Novel.de, n.d.).
The platform was used for two tests, the first is a normal gait on the footprint pad back and forth, and the emed® CL software calculates the average values for both the right and left feet and displays the data on the screen. The same procedure was repeated with the medical orthotic walker support (Novel.de, n.d.).
As shown in the result the average max force of the right leg for both volunteers without an orthotic walker was 513.38 N while with an orthotic walker, the average was 388.50 N, with a difference of 124.88 N (Figs. 5 and 7). On the other hand, the average max force of the left leg for both volunteers without an orthotic walker was 463.50 N while with an orthotic walker, the average was 397.50 N, with a difference of 66 N (Figs. 6 and 8). Hence, the gait analysis shows that the orthotic walker decreases the max force on each leg since the orthotic walker reduces the weight exerted on each leg. It decreased the maximum force exerted on the right leg by 24.33% and the maximum force exerted on the left leg by 14.24%.
Gait analysis of the right foot max force of the first volunteer with (right figure) and without (left figure) using the orthotic walker. Results of reports were obtained for gait analysis, and the max force in the right leg without a walker was 520.00 N while with the orthotic walker it was 377.00 N.
Gait analysis of the left foot max force of the first volunteer with (right figure) and without (left figure) using the orthotic walker. Results of reports were obtained for gait analysis, and the max force in the left leg without an orthotic walker was 508.25 N while with the orthotic walker it was 418.25 N.
Gait analysis of the right foot max force of the second volunteer with (right figure) and without (left figure) using the orthotic walker. Results of reports were obtained for gait analysis, and the max force in the right leg without an orthotic walker was 506.75 N while with the orthotic walker it was 400.00 N.
Gait analysis of the left foot max force of the second volunteer with (right figure) and without (left figure) using the orthotic walker. Results of reports were obtained for gait analysis, and the max force in the left leg without a walker was 418.75 N while with the orthotic walker it was 376.75 N.
The first volunteer showed a difference in max force between left and right feet without an orthotic walker of 11.75 N. While the difference between the left and right feet with an orthotic walker was 41.25 N. Moreover, The second volunteer showed a difference in max force between left and right feet without an orthotic walker of 88.00 N. While the difference between the left and right feet with an orthotic walker was 23.25 N. Hence, the average max force difference between the right and left legs without the orthotic walker was insignificant at 49.88 N, while with the orthotic walker was insignificant at 9 N.
Device design: electrical circuit
An electrical circuit has been designed to measure the load under the orthotic walker’s legs by the half-bridge load cells. To protect the strain gauge, 1000-ohm (Ω) resistors were attached to each load cell. Moreover, load cells were soldered to the HX711 amplifier to amplify the signal coming from the load cells, convert it to a digital signal, and then deliver the signal to the digital pins of the Arduino Uno chipset by a jumper wire (Fig. 9). The load cells convert exert loads into electrical signals, which are converted by the Arduino Uno chipset into a quantitative readable number, based on the operating software, then displayed on the Liquid Crystal Display (LCD) screen. Three feedback light emitting diodes (LEDs), one green and two red, were attached to the Arduino Uno digital pins to indicate the weight difference. To protect the LEDs and create an electrical load to draw current, 220-Ω resistors were used. A portable power bank was used as a power supply.
Device design: computer-assisted design and computer-assisted manufacturing modeling
The computer-assisted design resulted in three main parts; the first part is the mount (Fig. 10a) of the load cells to ensure that the inner part of each load cell has enough space for deflection and generating a signal. The second part is a cap (Fig. 10b—green portion) which is used to fit the orthotic walker legs in and exert pressure on the load cell below it. The third part is the base (Fig. 10b—gray portion), which supports the orthotic walker and acts as a base that houses the mount of the load cell and the cap on top of it. Figure 10c illustrates a cross-sectional view of the cap and the base.
CAD design of the orthotic walker leg tips by SolidWorks. (a) Mount of load cell, (b) cap and base of legs, and (c) cross section of cap and base. Abbreviation: CAD, computer-assisted design.
The 3D-printed orthotic walker leg tip model shows the load cell mount (Fig. 11a) and also the cap and base of the orthotic walker leg tip (Fig. 11b). Both models were 3D printed with a filament deposition manufacturing 3D printer utilizing PETG filament. Utilizing an infill layer thickness of 0.2 mm using PETG filament resulted in a total weight of about 150 g for the whole assembly, and it took about 15 h to print. For this study, a quantity of four tips was printed for a four-legged orthotic walker.
Device design: operating software
The operating software of the Arduino Uno microcontroller of the orthotic walker was developed utilizing C++ programming language. The software was configured to convert the exerted force into a mass with the unit of grams. Furthermore, the software was configured to mathematically add the exerted weight of each side together. That means, the exerted weight on the two load cells on the right side (front right and rear right load cells) of the orthotic walker were mathematically added to each other to calculate the total weight on the right side. Similarly, the exerted weight on the two load cells on the left side (front left and rear left load cells) of the orthotic walker was mathematically added to each other to calculate the total weight on the left side. The software was configured to show on the LCD the weight exerted on each side simultaneously with the actual exerted load.
After that, the total weight of each side was subtracted from each other by the software to calculate the overall balance of the patient using the orthotic walker. If the difference in weight exceeds 2000 g on either of the sides, a red LED light turns on at the corresponding side of the feedback device. If the difference in weight is <2000 g on either of the sides, a green LED light turns on in the middle of the feedback device. The software also takes into consideration the weight of the orthotic walker on the load cells to reflect the actual weight exerted by the patient on the orthotic walker.
The assembly of the walker
Figure 12 illustrates the fully assembled rehabilitation orthotic walker with a real-time visual feedback system of gait symmetry, which includes all components and parts previously described. A traditional orthotic walker was utilized as the body of the invention. The brown wooden box includes the Arduino Uno microcontroller, the LCD screen, and the three feedback LEDs (two red on the sides and one green in the middle). It was attached to the orthotic walker in a manner that the LCD screen and feedback LEDs are visually apparent to the patient while being used. Furthermore, the four 3D-printed leg tips were installed in replacement of the traditional rubber leg tips, to be able to measure the exerted weight on each of the four legs of the walker independently. For clarification purposes, cables were extended externally from the Arduino Uno microcontroller in the wooden brown box to the 3D-printed leg tips to provide power and acquire signal to/from the load cells in each 3D-printed leg tip.
Orthotic walker validity test
To validate that the orthotic walker measures the actual exerted weight on each side of the orthotic walker, known loads of 5, 10, 15, and 20 kg weights were utilized. Table 1 shows the results of the validity test.
Orthotic walker proof-of-concept
Figure 13 illustrates the feedback signal acquired from the orthotic walker with the feedback system. The first volunteer used the orthotic walker to walk 8 m in a straight line; 30 steps starting with the left leg were measured, in which the right leg did not record any exerted weight, which is the negative control. Additionally, there is a minor difference in the exerted weight on the orthotic walker between the left and right legs according to the load cell readings. The average of weight exerted on the orthotic walker with the feedback system by the first volunteer showed a difference between the right and the left legs (Fig. 13). The average difference is around 126 g between each leg, which is insignificant.
Graph from the orthotic walker with the visual feedback system showing the difference in the weight (grams) exerted on each leg while the volunteer is walking.
To prove the concept of the functionality of the orthotic walker with the visual feedback system, the three volunteers with TKR surgeries showed significant differences between each side of the exerted load on the orthotic walker. The average exerted weight on the left side (healthy limb side) of the orthotic walker of the first volunteer with TKR was 56.69 ± 0.86 kg [average ± standard deviation (SD)], while the average exerted weight on the right side (TKR limb side) of the orthotic walker was 35.19 ± 1.19 kg (average ± SD). The average exerted weight on the left side (healthy limb side) of the orthotic walker of the second volunteer with TKR was 47.72 ± 0.77 kg (average ± SD), while the average exerted weight on the right side (TKR limb side) of the orthotic walker was 33.74 ± 0.85 kg (average ± SD). The average exerted weight on the left side (healthy limb side) of the orthotic walker of the third volunteer with TKR was 50.88 ± 0.56 kg (average ± SD), while the average exerted weight on the right side (TKR limb side) of the orthotic walker was 34.93 ± 1.19 kg (average ± SD). Figure 14 illustrates the above-mentioned data.
DISCUSSION
It is estimated that there are more than 7.4 million people in the world who depend on walkers to assist them in their walking either due to a disability, old age, or as a part of rehabilitation following accidents and medical conditions (Abualait and Alnajdi, 2021). However, such prolonged use of walking assistive devices and heavy reliance on healthy lower limbs may cause negative gait disorders in patients. To overcome such an issue that might occur because of using the traditional orthotic walker, a real-time visual feedback system of the gait symmetry was designed, developed, and tested. This study was conducted with a sample of two healthy female volunteers and three female volunteers with TKR in their right knees to prove the concept of measuring the imbalance of the weight-bearing difference on each of the lower limbs.
For the two healthy volunteers, there was an insignificant difference in force while walking with and without the walker for each lower limb. The difference as mentioned above was 24.33% for the right leg and 14.24% for the left leg, for two healthy volunteers. This difference in force reduction between each leg might be due to the dominancy of one side of the lower limb over the other, or because it was the first time for them to use reciprocal walkers; therefore, practice to find their balance was needed. On the other hand, for the three volunteers with TKR in their right knees, the difference between the weight exerted on the left side of the orthotic walker (left healthy limb) is significantly higher than the right side of the orthotic walker corresponding to the right limb with TKR. Although those volunteers had their surgeries >5 years ago and used traditional reciprocal walkers in their post-surgery rehabilitation for a month or two, they still showed asymmetrical gait. This proves the concept of the functionality of the orthotic walker with the visual feedback system and emphasizes that it is needed to aid such patients in correcting their asymmetrical gait.
To validate that the orthotic walker measures the actual exerted weight on each side of the orthotic walker, known loads of 5, 10, 15, and 20 kg weights were utilized. Despite the 0.1% accuracy mentioned in the data sheet of the load cells’ manufacturer, the average error percentage was found to be around 9.17% which is a large error margin compared to the manufacturer data sheet. This might be due to the low quality of load cells or an unknown electrical circuitry malfunction. However, the orthotic walker was still able to show a significant difference between each side with the three volunteers with TKR surgeries. Error margin could be reduced by using better quality components and replacing generic Arduino Uno circuitry with custom-designed and implemented electrical circuit boards.
The design and development of the rehabilitation orthotic walker with a real-time visual feedback system here is just a proof-of-concept that a prototype is achievable and functional. Surrogate materials were used and preliminary designs were made. For a fully functional and commercially feasible orthotic walker with a visual feedback system, further development and tests are required to produce a minimum viable product (MVP). Such an MVP should utilize better quality materials and components and pass several characterization tests to establish the orthotic walker’s hardware and software’s validity and reliability (psychometric properties). Such psychometric properties include, but are not limited to, comparing forces with and without using the orthotic walker utilizing a gait analysis system such as the emed® platform utilized above and comparing differences to the readings of the orthotic walker. Also, attaching a range of known certified weights to the walker and comparing its readings to the actual weights. Furthermore, additional clinical verification and validation of the orthotic walker with the visual feedback system must be done with a larger sample size of patients who had lower limb surgeries and used traditional walkers and with patients who just had lower limb surgeries and have not used any walkers yet.
The use of a traditional walker increases the base of support and reduces swing and load on the lower limbs (Fast et al., 1995). Yet, there was a difference between the average weight measured on each side of the orthotic walker with the feedback system (126 g), as illustrated in Figure 15. Therefore, simple yet informative feedback LEDs were included in the design to provide visual feedback for the patient. This visual feedback is simple to interpret and act upon by the patient to rebalance their gait without trying to interpret readings. Such a simple visual feedback system would be helpful for elder patients who had lower limb surgeries.
A walker in rehabilitation aims to increase the functional ability of patients to walk without negatively affecting their gait symmetry. However, practically, patients with walking disabilities or after lower limb surgeries, usually increase their body load on the healthy limb more than the disabled limb, which later may result in asymmetric gait (Cichy et al., 2008; Afzal et al., 2015). Therefore, the developed feedback system reports the amount of body loading on each side (right and left sides) while walking, which can be used by health practitioners to analyze their patient’s gait and recommend how to distribute their body load on their lower limbs. Also, the developed system can be adapted to any type of assistive walking device a health practitioner would use.
Several studies (Fast et al., 1995; Bateni and Maki, 2005; Costamagna et al., 2017) have shown that the walker can bear from 85% to 100% of the body weight depending on the individual’s strength and the cause of the disability. Healthy people may use it to increase stability, so it bears 10-30% of their weight, while others use it to reduce the load on their lower limbs because of their muscle weakness; here, the reciprocal walker may bear 85-100% of their body weight (Bateni and Maki, 2005).
Despite the benefits of assistive devices, they have several disadvantages. Some users may abandon their devices (30-50%) in a short time, which results in an increased risk of falling. In patients with neurological disorders that cause cognitive impairment, it is difficult to carry out more than one task at the same time, such as walking with an assistive device and talking or changing direction (Martins et al., 2012). There may be negative aspects of using the walker while walking, such as reducing the natural swing of the arm and abnormal bending of the back. Additionally, the walker should not be used in narrow, crowded places, or on stairs (Van Hook et al., 2003).
CONCLUSION
The outcome of this study was the conceptualization, design, prototype, and testing of the proof-of-concept of a rehabilitation orthotic walker with a real-time visual feedback system to aid in gait symmetry. The system utilizes load cells, to measure the weight difference between each side of the lower limbs. Also, it utilizes Arduino Uno as a microcontroller, an LCD screen, and red and green LEDs to provide real-time feedback for the patient on their gait symmetry. The feedback depends on the difference between the loaded weights on each side of the legs of the orthotic walker. From this, feedback is visualized for the patient by the LEDs to try to counter their asymmetry for a better symmetrical gait.