Soft exosuit
The multi-joint soft exosuit is designed to assist with plantarflexion, hip flexion, and hip extension while walking [28]. As shown in Fig. 1a, the exosuit apparel components consist of a waist belt, two thigh pieces, two calf wraps, two dynamic multi-articular straps connecting the front of the waist and the back of the calf, and two boot covers wrapping around the wearer’s ankle. The multi-articular strap is designed to distribute assistive forces applied at the ankle between the calf wrap and the waist belt [28]. The total mass of all suit components for a size medium is 1.1 kg, including two metal brackets bolted to the back of military boots. As shown in Fig. 1b, this textile architecture creates two different load paths on each leg: a multi-articular load path assisting with plantarflexion and hip flexion during push-off and a hip extension load path assisting with hip extension in early stance.
Hardware implementation
A mobile actuation system was developed to generate assistive forces and mounted at the lower back of a military rucksack [28]. As shown in Fig. 1c, the actuation system consists of four independent actuator units, two for multi-articular load path and the other two for hip extension load path. Each actuator unit is comprised of an Emoteq frameless 6-pole motor (Allied Motion Inc., Amherst, NY, USA), a Spiroid helicon gear box (38:1 gearing ratio for multi-articular actuator units and 36:1 for hip extension actuator units; Illinois Tool Works, Inc., Glenview), and a 55-mm diameter multi-wrap pulley. The forces generated by the actuation system are transmitted to the exosuit via Bowden cables; when the motor retracts the Bowden cable, the distance between two attachment points on the exosuit is shortened, creating assistive forces along the corresponding load path. The actuation system including Bowden cables weighs 5.9 kg, and a 48 V-8 A∙hr. Li-Po battery pack (2.0 kg) stowed in the rucksack was used to power the actuation system that would be sufficient for approximately 8 km of continuous walking operation.
On each leg, a linear daisy-chain harness including three inertial measurement units (IMU; MTi-3 AHRS; Xsens Technologies B.V., Enschede, Netherlands) and two load cells (LSB200; Futek Advanced Sensor Technology Inc., Irvine, CA, USA) was placed to collect real-time data from the exosuit and the wearer. As shown in Fig. 1a, the IMUs were attached to the wearer’s thigh, shank, and foot to measure the sagittal-plane orientation and the angular velocity of each segment, while the load cells were mounted in series with the Bowden cables to monitor the level of assistive force delivered to the wearer through the exosuit. The full sensor harnesses including all sensors weigh 0.3 kg.
Biologically inspired control
As with the previous-version exosuits [34, 35], the controllers for the multi-articular and hip extension load paths both performed a force-based position control of the Bowden cables to generate assistive forces. Inspired by biological behavior of the target joints, the controller applies the assistance by retracting the Bowden cable during a target period within a walking cycle. As shown in Figs. 2 and 3, the cable position profiles were defined by four timing parameters, T0, T1, T2, and T3, which are represented as percentage of a gait cycle (% GC) and two cable position parameters, PosOffset and PosMax, which are iteratively adjusted on a step-by-step basis [34, 35]:
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T0: the start timing of the controller within a gait cycle.
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T1: the onset timing of the active cable retraction.
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T2: the completion timing of the active cable retraction.
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T3: the start timing of the cable release.
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PosOffset: Bowden cable position right before the active cable retraction (at T1).
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PosMax: Bowden cable position when the cable is fully retracted (from T2 to T3).
Multi-articular controller (MA)
The controller for the multi-articular load path was designed to deliver the majority of assistance during ankle push-off [34]. As shown in Fig. 2, the controller first detected the heel strike using the first peak of sagittal-plane gyro signal from the foot IMU, which happens approximately at 5% GC [34]. This event was used as the start of the multi-articular controller, T0MA (i.e. T0MA = 5% GC), and starting from T0MA, the motor shortened the cable up to PosOffsetMA at a constant speed of 394 mm s− 1 (65% of the maximum cable speed of the multi-articular actuator unit). Note that this cable speed was determined during pilot experiments to strike balance between being fast enough to reach PosOffsetMA during early stance and not being excessively fast to not restrict the wearer’s dorsiflexion. After reaching PosOffsetMA, the controller maintained this cable position until the onset of the active cable retraction, T1MA (automatically tuned; details in the following section). Then, the cable was actively retracted up to PosMaxMA until the completion timing of the active cable retraction, T2MA (automatically tuned; details in the following section). Then, the controller held the cable position constant until the load cell detects a force drop as the ankle further plantarflexes, and this event was used as the start of the cable release, T3MA. Starting from T3MA, the motor released the cable at the maximum speed of 606 mm s− 1 to its zero position where the cable is completely slack, in order to not restrict the wearer during swing phase. After reaching the zero position, the motor maintained this cable position until the next heel strike detection.
At the end of each stride, the controller either increased or decreased PosOffsetMA and PosMaxMA for the next stride by comparing the desired and the measured force. For example, PosOffsetMA was adjusted to deliver a peak force of 75 N (equivalent joint moment of approximately 7.5 Nm) between T0MA and T1MA, to consistently pretension the cable before the active cable retraction. PosMaxMA was adjusted to deliver a peak force of 400 N (equivalent joint moment of approximately 40 Nm) between T1MA and T3MA, as a primary means to deliver assistance during the active cable retraction.
Hip extension controller (HE)
The controller for the hip extension load path aimed at applying assistance in early stance while hip extensor muscles are active. The hip extension controller used constant timing parameters (T0HE, T1HE, T2HE, T3HE) for all users without parameter tuning, whose values were from the experimental condition with the largest metabolic benefit in Ding et al. where the effect of four different sets of timing parameters were compared for an exosuit assisting hip extension [35]. Unlike the multi-articular controller, these timing parameters are represented as percentage of a gait cycle segmented by maximum hip flexion event (% GCMHF) detected by the thigh IMUs; note that the maximum hip flexion happens approximately 12% earlier than heel strike (i.e. % GCMHF ≈ % GC - 12%) [35]. As shown in Fig. 3, the controller first detected the maximum hip flexion using the thigh IMU and used this event as the start of the controller (i.e. T0HE = 0% GCMHF). Then, the motor was controlled to shorten the cable up to PosOffsetHE at a constant speed of 800 mm s− 1, which was the maximum cable speed of the hip extension actuator. After reaching PosOffsetHE, the controller maintained this cable position until 7% GCMHF (i.e. T1HE = 7% GCMHF). Then, the motor further retracted the cable up to PosMaxHE until 28% GCMHF (i.e. T2HE = 28% GCMHF), and held the cable in this position until 34% GCMHF (i.e. T3HE = 34% GCMHF). Finally, the motor released the cable to its zero position, using the maximum cable speed of 800 mm s− 1 similarly to the multi-articular controller. The PosOffsetHE and PosMaxHE were adjusted at the end of each gait cycle, to deliver a peak force of 10 N (equivalent joint moment of approximately 1 Nm) between T0HE and T1HE and a peak force of 300 N (equivalent joint moment of approximately 30 Nm) between T1HE and T3HE, respectively.
Augmentation-power-based control parameter tuning
In order to customize the multi-articular assistance for each individual, an online parameter tuning method was developed which searches the control parameters that maximize the positive augmentation power delivered at the ankle. This assumes that the positive ankle augmentation power can be an indicator of the magnitude of assistance delivered at the ankle, which in turn may have a positive correlation with the corresponding metabolic benefit [6, 10, 19, 29,30,31,32,33]. Of note, in this study the average positive augmentation power was calculated by dividing the positive augmentation work over a gait cycle by the stride time. The positive augmentation work may also indicate the amount of assistance delivered to the joint, but it may significantly vary with the wearer’s cadence. In contrast, positive power is less affected by variability in cadence, making it a more robust objective metric for control parameter tuning (See Additional file 1 for further discussion).
Tuning parameter selection
Among the control parameters defining the cable position profile of the multi-articular controller, T1MA (onset timing of the active cable retraction) and DMA (T2MA - T1MA; duration of the active cable retraction) were selected as the parameters to be tuned for each individual. As highlighted in green in Fig. 2, these parameters play an important role in determining the cable position profile during the active cable retraction phase, where the majority of ankle assistance is delivered during push off. In addition, in pilot experiments T1MA and DMA showed higher sensitivity to the changes in positive ankle augmentation power than other control parameters, highlighting the importance of customization of these parameters. The initial parameter ranges were set to 35–50% GC for T1MA and 7.5–22.5% GC for DMA, where the actuation system could generate the desired level of peak assistive force (400 N) at the ankle joint. With this parameter range the multi-articular controller was capable of creating force profiles ranged approximately from 35 to 65% GC, which sufficiently covers the phase of positive biological ankle power while walking.
Positive augmentation power measurement
While walking with the exosuit active, the instantaneous ankle augmentation power was calculated from the ankle joint velocity (measured by the foot and shank IMUs) and the assistive force (measured by the multi-articular load cell), assuming a constant lever arm of 10 cm at the ankle. The positive augmentation work over a stride was calculated by integrating the positive area under the instantaneous power curve over a gait cycle, and finally the positive augmentation power was calculated by dividing the positive work by the stride time [6, 9, 30, 34, 36]. In this study, while each parameter setting was given to the wearer for 45 strides, the positive augmentation power for each condition was averaged over the last 30 strides (Note that, in pilot experiments, it took about 10 strides to reach a steady-state positive augmentation power value when a new set of parameters were applied).
Online parameter tuning algorithm
A simple online parameter tuning algorithm based on 2-D grid search similar to gradient descent was developed and used for this study. During the tuning process, subjects continuously walked with the exosuit on a treadmill, and the multi-articular controller applied 16 different parameter settings in series, searching the parameter values that maximize the positive augmentation power delivered at the ankle. First, the controller swept the initial four conditions, where T1MA was varied over 35, 40, 45, and 50% GC while DMA was held constant at 15% GC. These values were chosen by varying T1MA with 5% interval within its initial range (35–50% GC) while holding DMA constant at the mid-point of its initial range (7.5–22.5% GC). Among the four values of T1MA, the controller selected the setting where the largest positive augmentation power was delivered to the ankle. Of note, due to the hardware limitations (specifically motor power), during this selection step the controller was designed to exclude certain parameter settings where the exosuit was limited from achieving a desired peak force of 400 N. Next, the controller applied another four conditions by varying DMA with 5% interval within its range (i.e. DMA = 7.5, 12.5, 17.5, and 22.5%) while holding T1MA constant at the previously selected value. Similarly, among the four values of DMA, the controller selected the value with the largest positive ankle augmentation power. Following this alternate parameter search scheme, another set of exploration over both T1MA and DMA was repeated with a reduced interval of 2.5%. Finally, the parameter setting where the positive ankle augmentation power was maximized among the 16 conditions was chosen for each individual. Of note, the total number of conditions included in the tuning process was determined during pilot experiments, where we found that a modification of control parameters smaller than 2.5% GC did not induce a substantial change in the positive ankle augmentation power. In addition, the total 16 conditions allowed for the entire tuning process to be done in about 15 min, which is short enough to not induce significant fatigue of the wearer during the continuous walking trial.
This relatively simple parameter tuning algorithm presents several positive attributes. At this stage, the focus of the study was on testing the feasibility of the augmentation-power-based control parameter tuning approach, so a simple method aimed at proving the general concept was preferred, as opposed to applying a more sophisticated and efficient optimization technique. In addition, as this method sequentially varies either one of the two control parameters while holding the other constant, the tuning process is comprised of a series of single parameter sweeps. Compared to other multi-dimensional optimization techniques that may vary multiple parameters at the same time, this approach yields data that may provide insight on the individual parameter’s effect during the tuning process.
Experimental protocol
Seven healthy male adults with prior experience walking with the exosuit participated in this study (age 31.0 ± 7.3 years; mass 83.0 ± 7.9 kg; height 1.80 ± 0.04 m; mean ± SD). The Harvard Longwood Medical Area Institutional Review Board approved the study, and all participants provided written informed consent. The study consisted of a single-day experimental session, involving walking on a treadmill at 1.50 m s− 1 carrying a loaded military rucksack with a total mass of 6.8 kg, with and without wearing the exosuit (Fig. 4). Note that a fixed walking speed was used in this study, because variation in walking speed by itself may change the positive ankle augmentation power. The amount of load carried during this experiment was selected to not induce fatigue in the participants. At the beginning of the session, a 4-min standing trial was performed to collect steady-state standing metabolic cost. Participants then underwent a 15-min control parameter tuning process explained above. After the tuning process, participants completed three 5-min experimental conditions: loaded walking with the exosuit unpowered (EXO-OFF), loaded walking with the exosuit active using individualized parameters found by the augmentation-power-based parameter tuning (EXO-ON), and loaded walking without wearing the exosuit (NO-DEVICE). The two exosuit conditions were randomized, but NO-DEVICE condition was always completed last to minimize exosuit donning and doffing time during the session.
Measurement and data processing
A portable indirect calorimetry system (K4b2, COSMED, Rome, Italy) was used to measure the metabolic cost of walking. Metabolic power was calculated using a modified Brockway equation [37] and averaged over the last 2 min of each condition. For each walking condition, net metabolic rate was calculated by subtracting the metabolic power during standing and then normalized to each participant’s body mass. Percent net metabolic benefit was calculated as the reduction in net metabolic rate for EXO-ON condition compared to NO-DEVICE condition, while gross metabolic benefit was calculated compared to EXO-OFF condition:
$$ Net\ Metabolic\ Benefit\ \left[\%\right]=\frac{\left(N{O}_{DEVICE}\right)-\left( EX{O}_{ON}\right)}{\left(N{O}_{DEVICE}\right)-(STANDING)}\times 100\% $$
$$ Gross\ Metabolic\ Benefit\ \left[\%\right]=\frac{\left( EXO\_ OFF\right)-\left( EXO\_ ON\right)}{\left( EXO\_ OFF\right)-(STANDING)}\times 100\% $$
Inter-subject mean and standard error of the mean (SEM) were calculated for the net metabolic rate and the percent metabolic reduction. Two-sided paired t-tests (significance level α = 0.01; MATLAB, MathWorks Inc., Natick, MA, USA) were used to test statistical significance of the difference in net metabolic rate between two conditions.