**Abstract**

Customized insoles are commonly prescribed to prevent or treat a variety of foot pathologies and to reduce foot and lower limb fatigue. Due to the patient-specific design and production of such orthotics, the concept of self-selected customized orthotics (SSCO) has recently been developed. The goal of this study was to assess the impact of SSCO technology on several physiological and biomechanical variables during uphill power walking. Thirty male participants underwent an uphill power walking intervention at constant speed in two insoles conditions (control and SSCO). The electromyographic (EMG) activity of their right gastrocnemii and vastii muscles was measured. Perceived fatigue was assessed every 5 minutes and the intervention stopped when the targeted fatigue level was reached. Baseline and post-intervention assessments were also performed. Sixty-three percent of the participants experienced an improvement in foot fatigue while wearing the SSCO. The foot arch seemed to collapse less when participants wore the SSCO, but statistical significance was not reached. The changes in mean EMG activity was not consistent between the 50% isometric contraction and the walking trial. In conclusion, while some interesting trends were observed when wearing SSCO, further investigations should be performed to try and reach statistical significance.

**Keywords:** orthopedics, custom orthotics, orthotics, lower limbs, insoles, walking, fatigue, neuromuscular, biomechanics

### **1. Introduction**

Customized insoles have been shown to reduce pain [1], improve static balance [2] and redistribute pressure [3, 4]. As a result, they are commonly prescribed to prevent or treat a variety of foot pathologies [5]. For instance, wearing custommade foot orthoses has been reported to reduce medial foot loading and/or improve the condition of people with patellofemoral pain [6]. Research has also shown that the use of custom-made laterally wedged insoles can reduce pain, enhance joint function and improve quality of life in older adults affected by medial knee osteoarthritis [7]. Customized insoles have also demonstrated the ability to prevent deformations and necrosis of the foot by decreasing forefoot pressure [8–12], hence reducing the risks of ulceration for patients with diabetes and neuropathy [13, 14]. Custom-made inserts can also be prescribed to reduce areas of peak pressure in

individuals with high medial longitudinal arches, leading to a lower risk of developing pes cavus deformities [15].

Besides their ability to improve people's health, comfort and quality of life, customized insoles are also designed to reduce the sensation of foot and lower limbs fatigue. For example, see [16], investigated the effect of custom-made orthotics in healthy participants undergoing long periods of standing and walking at work. The results reported a significant reduction in foot fatigue reflected by 68% of the population experiencing less foot discomfort at the end of the day, and by 60% of the participants reporting more comfort at work when wearing customized orthotics. Another study by, see [15], studied the impact of customized insoles on a population of females with idiopathic pes cavus during gait. They reported that the integrated electromyography (EMG) activity of four leg muscles (i.e. tibialis anterior, gastrocnemius medialis, rectus femoris and biceps femoris) decreased after wearing the custom-made orthotics. Also, see [17], studied the impact of insoles with custom arch support during uphill and downhill walking for individuals with flatfoot conditions. Their findings showed that added arch support led to a significant decrease in peak oxygen uptake (VO2), as well as a potential reduction in the activity of the rectus femoris. This indicates that wearing insoles with customized arch support could potentially improve motor control efficiency, and hence reduce fatigue in the lower extremities during gait.

In summary, multiple scientific evidence has demonstrated that custom-made insoles can positively impact people's health and quality of life. Yet, the patient specific design and production of such orthotics remains a potential limitation. Due to the known deformability of the foot [18–20], customized orthotics were originally molded based on a foot cast taken under different weight-bearing conditions [3]. With the constant advancements in 3D scanning and 3D printing technologies, the development of customized insoles is now being facilitated by the combined use of computer-aided design and computer-aided manufacturing (CAD-CAM). Nevertheless, the design and production of custom-made orthotics still require an in-depth examination with a specialist involving a variety of measurements, which can be time-consuming and potentially costly.

As a result, the concept of self-selected customized orthotics (SSCO) has recently been developed and introduced in stores and pharmacies. This concept is based on the use of an automated kiosk (Dr. Scholl's®, Bayer Healthcare, LLC, Whippany, NJ, USA) with embedded plantar pressure scan that can measure foot size, arch type and weight. Using the corresponding measures, the kiosk's recommendation engine can pre-select a specific insole design among a finite set of prefabricated orthotics with different arch and heel support characteristics. Such a system could represent an interesting opportunity to extend the accessibility of customized insole technology. However, conversely to traditional custom-made insoles, no investigation has yet measured the potential benefits of wearing SSCO. This study was designed to assess the impact of this new insole technology on several physiological and biomechanical variables during gait. More specifically, this study focuses on how SSCO can potentially reduce the perception of fatigue during uphill power walking.

### **2. Methods**

#### **2.1 Recruitment and testing conditions**

This study was approved by the Conjoint Health Research Ethics Board of the University of Calgary (Ref: REB17-0875\_MOD5). A total of 30 male participants (mean age: 26 years SD 5; mean BMI: 23.9 SD 2.7; shoe size: US 9–11) with no history of insole related condition/disorder, were tested on two separate days with

#### *Impact of Self-Selected Customized Orthotics on Lower Limbs Biomechanics DOI: http://dx.doi.org/10.5772/intechopen.94233*

a minimum of 48 hours between sessions to allow full recovery from the walking intervention. Participants were consistently scheduled at the same day time to reduce the risk of impacting their energy level and were asked to wear the same pair of running shoes during each session. Prior to testing, each participant read and signed a consent form.

Two different insole conditions were evaluated in a randomized order, including a control (i.e. no insole added, CTRL) and a SSCO with custom arch support (Custom Fit®, Dr. Scholl's®, Bayer Healthcare, LLC, Whippany, NJ, USA). The selected SSCO were built off three layers: a soft top cloth for comfort and durability, a cushion layer to disperse foot pressure and reduce shocks, and a 3D arch support dual layer to best fit the morphology of each individual's arch. For each shoe size, four different SSCOs were available with different arch support characteristics. For every participant, the best SSCO fit was selected based on weight (i.e. more or less than 170 lbs) and arch type (i.e. low, medium or high arch).

#### **2.2 Anthropometrics and subjective evaluations**

Upon the participant's arrival, an anthropometric evaluation was performed where variables such as height, weight, foot width and arch height were measured.

#### **2.3 Baseline assessments**

Prior to testing, participants were asked to fill out a questionnaire to assess the intensity of their baseline fatigue using a 0–5 Likert scale (**Table 1**).

Surface bipolar Ag-AgCI EMG electrodes (Norotrode Myotronics-Noromed Inc., Kent, WA, USA) with a diameter of 10 mm and an inter electrode spacing of 22 mm were positioned on the muscle bellies of the gastrocnemius lateralis (GL) and medialis (GM) of the right leg (**Figure 1**). To enhance signal conductivity, the corresponding skin surfaces were shaved and cleaned using abrasive tape and isopropyl wipe prior to electrode positioning. According to the SENIAM guidelines [21], each electrode was placed in the direction of the underlying muscle fibers.

Following electrode placements, each participant was placed lying prone in a horizontal position on an isokinetic dynamometer (Biodex System 4, Biodex Medical Systems, USA) with the right foot fixed to a plantarflexion attachment and the lateral malleolus aligned with the centre of rotation of the dynamometer. The EMG activity of the GL and GM muscles was recorded at 2400 Hz during two


#### **Table 1.**

*Likert scale (0–5) used to define the level of perceived fatigue for each participant.*

#### **Figure 1.**

*Left: EMG electrodes placement on the gastrocnemius lateralis (GL) and medialis (GM) - right: EMG electrodes placement on the vastus lateralis (VL) and medialis (VM).*

15-second isometric plantarflexion trials performed at 50% of the participant's maximal strength. To ensure a consistent torque output between trials and testing sessions, the maximal torque output of each subject was measured during the first day using two maximal voluntary contractions (MVC) trials. The corresponding value was then used to provide torque visual feedback during each 50% sustained contraction trials.

Participants were then asked to remove their shoes and socks and perform three 10-second standing trials and six walking trials (three steps per foot) on a foot pressure scan (Currex Footplate, Currex GmbH, Germany).

#### **2.4 Walking intervention**

The walking intervention was defined as a power walking trial on a 4° inclined treadmill at a constant speed of 4mph. Such settings were deemed sufficient - based on preliminary testing performed on seven volunteers - to induce fatigue in the feet and legs within a period of 30 to 60 minutes.

Prior to the intervention, additional EMG electrodes were placed on the vastus lateralis (VL) and vastus medialis (VM) (**Figure 1**). To detect heel strike, a one-dimensional (1D) accelerometer (sampling rate: 2400 Hz, encapsulated in a 20/12/5 mm plastic shell, measuring range: ± 50 g, frequency response: 0–400 Hz, mass: < 5 grams, ADXL 78, Analog Devices, Inc., Norwood, USA) was taped on the participant's right heel and synchronized with the EMG recordings.

Prior to the intervention, a 6-minute warm-up trial was performed with increasing walking speed and inclination angle (i.e. 2 minutes at 3mph and 1° incline, 2 minutes at 3.5 mph and 2.5° incline, and 2 minutes at 4mph and 4° incline). After warm-up, EMG activity of the GL, GM, VL and VM were recorded at 2400 Hz respectively for segments of 5 minutes. At the end of each segment, the participant was asked to rate his level of perceived fatigue using the same 0–5 Likert scale as the one used during the baseline assessments (**Table 1**). During the first testing session, the intervention stopped when the subject reached a fatigue

*Impact of Self-Selected Customized Orthotics on Lower Limbs Biomechanics DOI: http://dx.doi.org/10.5772/intechopen.94233*

level of 4 (described as heavy/sore legs and/or feet leading to voluntary changes in walking pattern to relieve muscles) on the perceived fatigue scale. The corresponding time was used to define the duration of the intervention during the second testing session. If a participant was not able to reach a fatigue level of 4 after a duration of 60 minutes or reached a fatigue level of 5 (i.e. extremely sore legs and feet very leading to the immediate need to stop the intervention), prior to 30 minutes, the intervention was stopped, and the corresponding data was not used in the analysis.

#### **2.5 Post-intervention assessments**

Immediately following completion of the intervention, each participant performed the same tests as describe in the baseline assessments section, starting with the foot pressure scans (standing and walking), followed by one isometric contraction trial. At the end of each session, participants were asked to rate their postintervention perceived fatigue, as well as the comfort of the tested insoles (overall, heel, arch, forefoot).

#### **2.6 Data processing**

Data were all processed using custom-written Matlab codes (R2017a, MathWorks, Inc.).

#### *2.6.1 Foot pressure scans*

For each standing and walking trial performed on the foot pressure scan, the corresponding static and dynamic arch indices were calculated using the method described by, see [22], which defines the arch index as the ratio between the midfoot area (i.e. middle third of the entire footprint excluding the toes) and the area of the whole foot (toes excluded).

#### *2.6.2 EMG*

A wavelet transform using 20 non-linearly scaled wavelets (centre frequencies: 1.38, 3.86, 7.54, 12.42, 18.47, 25.69, 34.08, 43.61, 54.30, 66.12, 79.09, 93.19, 108.41, 124.76, 142.24, 160.83, 180.55, 201.37, 223.31, 246.35 Hz) was applied to the raw EMG signals recorded during each isometric contraction trials. The mean EMG frequency of each muscle was calculated using the power spectrum of the corresponding wavelet transformed signal and compared between baseline and post-intervention.

A custom-written heel-strike detection algorithm was applied to the walking EMG data to isolate each step within a defined window (i.e. 300 ms before and 600 ms after heel strike). For each step and muscle, the active portion of the EMG signal was selected using fixed time windows (i.e. from 75 ms before to 150 ms after heel strike for the GL and GM, and from 195 ms to 555 ms after heel strike for the VL and VM). The resulting active portions were then wavelet transformed using the method described above, and the corresponding power spectra were averaged for the first (non-fatigued) and last (fatigued) minute of recording.

#### **2.7 Data analysis**

The impact of fatigue was assessed for each variable as the relative change from non-fatigued to fatigued stages (i.e. baseline to post-intervention, first to last

minute) and expressed as a percentage. A one-tailed paired T-test with alpha = 0.05 was performed to compare between insole conditions.
