Implementation of precedence walking assistance mechanism in exoskeleton with only vertical ground reaction forces D. Cha, S. Oh, K.I. Kim, K.-S. Kim and S. Kim A more rapid detection method for step initiation is an important challenge for muscle force reduction in lower limb exoskeletons. Many studies have attempted to detect step initiation faster via either the precedence walking assistance mechanism or the shadow walking assistance mechanism. Although the precedence walking assistance mechanism is the fastest for the detection of step initiation, this mechanism has limitations while using biosignals. As a result, many studies have attempted to detect step initiation with the shadow walking assistance mechanism as soon as possible. A precedence walking assistance mechanism has been implemented for step initiation in the Unmanned Technology Research Centre Exoskeleton (UTRCEXO) based on gait analysis without using any biosignals. Success was achieved in reducing the muscle force of the operator.
Introduction: A lower limb exoskeleton is a mechanical active device that enables the operator to walk more comfortably by reducing the muscle force required [1]. Many studies have attempted to reduce the muscle force of the operator during step initiation by using one of the two approaches: the precedence walking assistance mechanism and the shadow walking assistance mechanism [2, 3]. The precedence walking assistance mechanism detects the operator’s step initiation prior to the operator’s visible movements, such as heel-off or toe-off, by using biosignals. The robot suit Hybrid Assistive Limb (HAL) implements the precedence walking assistance mechanism by using electromyography. The HAL detects the operator’s step initiation before the corresponding visible movements occur [1]. However, the HAL has limitations in further development of the exoskeleton with biosignals, because of the issues encountered with biosignals, such as low reliability, long calibration times for each operator and so on. The shadow walking assistance mechanism detects the operator’s step initiation after the operator’s visible movements occur, such as the heel-off event or the toe-off event. The RoboKnee detects the operator’s step initiation based on the heel-off event, when the heel is lifted just before the front end of the foot leaves the ground, by using load cells installed in their shoes [1]. The Berkeley Lower Extremity Exoskeleton (BLEEX) detects the operator’s step initiation with the toe-off events, when the toe leaves the ground, by using a foot switch installed in their shoes [1]. These approaches are reliable because they detect step initiation after visible movements occur related to step initiation. However, the operator must use her/his muscle force for step initiation with the exoskeleton. Also, it needs a control algorithm based on the relatively good dynamics model of the system and more sensors. In this Letter, we propose a new approach for implementing the precedence walking assistance mechanism for the step initiation without using any biosignals in the Unmanned Technology Research Centre Exoskeleton (UTRCEXO). We analysed the human gait from a quiet standing position to the first step by using three force plates and motion capture devices. We found that two vertical ground reaction force (GRF) events occur before visible movement occurs. With these vertical GRF events, we implemented the precedence walking assistance mechanism for the step initiation in the UTRCEXO and demonstrated the reduction of the muscle force required for the step initiation. Experimental setup: A 10 m-long and 1 m-wide walkway with motion capture cameras (Motion Analysis, Hawk® ) and three force plates (AMTI, AccuGait® ) was set up. We measured the kinematic data by using motion capture cameras at a 200 Hz sampling frequency, and the collected motion capture data were filtered by using a fifth-order Butterworth lowpass filter with a cutoff frequency of 10 Hz. The GRF data were measured by three force plates at a 200 Hz sampling frequency, and the collected GRF data were filtered by using a fifth-order Butterworth lowpass filter with a cutoff frequency of 30 Hz. Also, we developed the insole-type force-sensing resistors (FSRs) to obtain similar GRF patterns based on the force plates and utilised them to implement the precedence walking assistance mechanism. Fig. 1a shows the system of the insole-type FSRs. It consists of two channel FSRs for each foot on heel and toe, and a microcontroller unit. Its
force sensitive range is from 100 g to 10 kg and its pressure sensitive range is from 1.5 to 150 psi. The resolution of the insole-type FSRs is 12-bit and the sampling rate of the insole-type FSRs is 10 Hz. Fig. 1b shows the operator equipped with the UTRCEXO. The UTRCEXO has 150 W DC motors at each knee and hip joint. As soon as the UTRCEXO detects the operator’s step initiation with the insole-type FSRs, the UTRCEXO transmits each required joint torque as a reference torque to the motor controller.
a
b
Fig. 1 Insole-type FSRs (Fig. 1a) for UTRCEXO (Fig. 1b)
Methodology: Seven healthy subjects (seven males) volunteered to participate in this study. They had no postural problem and agreed to the informed consent approved by the Institutional Review Board of the KAIST prior to the test. Their average height and weight were 1.75 ± 0.03 m and 75.1 ± 7.94 kg, respectively. First, the subjects stood with both feet on the force plates, and walked starting with the right foot on the walkway with the instruction to walk with their preferred step velocity. We calculated the GRF from the stance phase to the first step by using three force plates. Each subject performed 10 trials and we collected a total of 70 datasets. Secondly, the subjects had insole-type FSRs installed in their shoes. They stood with both feet on the ground, and walked starting with the right foot with the instruction to walk with their preferred step velocity. Each subject performed 20 trials and we collected a total of 140 datasets. Lastly, the subjects were equipped with the UTRCEXO, as shown in Fig. 1b, and walked starting with the right foot with the instruction to walk with their preferred step velocity. Results: First, we obtained the two vertical GRF events from the force plates for the seven subjects, as shown in Fig. 2. These were the first vertical GRF intersection between the left foot and the right foot (○), and the vertical GRF of the first step decreased rapidly after the peak value, followed by the heel-off and the toe-off (□). We could always see these particular GRF events before any visible movements occur, such as heel-off, knee flexion and toe-off. We attempted to detect the step initiation with these vertical GRF events. Table 1 shows the comparison between our approach and other approaches to detect the step initiation. Clearly, the findings indicate that the two particular vertical GRF events always occur for the step initiation and it can be used to detect the step initiation before visible movements occur without using any biosignal. Secondly, we always obtained similar events from the insole-type FSRs, as shown in Fig. 3. We could see not only the intersection event between the left foot and the right foot (○), but also the peak value followed by the heel-off and the toe-off (□). This result clearly indicates that we can implement the precedence walking assistance mechanism for step initiation in the UTRCEXO without using any biosignals by using the insole-type FSRs simply and reliably. Last, we implemented the precedence walking assistance mechanism for the step initiation in the UTRCEXO without using any biosignals by using the insole-type FSRs. As a result, the operator could reduce the muscle force for the step initiation, as shown in Fig. 4. In Fig. 4, the positive value of the y-axis is related to how much the operator uses her/his muscle force during the step initiation.
ELECTRONICS LETTERS 30th January 2014 Vol. 50 No. 3 pp. 146–148
Table 1: Comparison results between our approach and other approaches with particular vertical GRF events
vertical GRF pattern
800
visible movements
invisible movements
700
right foot (leading) left foot (trailing)
600
Detection mean time (s) Standard deviation
GRF, N
500
Our approach Heel-off approach Toe-off approach 0.612 0.742 0.872 0.019 0.033 0.034
t-Value 400 300
heel-off(R)
heel-off(L)
0.0005
Conclusion: In this Letter, we propose a new approach to implement the precedence walking assistance mechanism in the UTRCEXO without using any biosignal based on the human gait pattern analysis.
200 100
0.0069
We were able to detect step initiation faster than other approaches *Significance level p < 0.01
toe-off(L) toe-off(R)
0 heel-strike(R) –100
0
0.5
1.0
toe-off(R)
1.5
time, s intersection event
2.0
2.5
Acknowledgment: This work was supported by the Unmanned Technology Research Centre (UTRC).
peak event
Fig. 2 Vertical GRF patterns of subjects from force plates There are two important GRF events that we can utilise to detect step initiation of subjects faster before visible movements occur
© The Institution of Engineering and Technology 2014 18 November 2013 doi: 10.1049/el.2013.3830 One or more of the Figures in this Letter are available in colour online. D. Cha, K.-S. Kim and S. Kim (Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 305-701, Republic of Korea)
trailing limb (L)
E-mail:
[email protected] S. Oh and K.I. Kim (Department of Electrical Engineering, Myong Ji University, San 38-2, Nam-Dong, Yongin, Kyunggi-Do 449-728, Republic of Korea)
leading limb (R)
References
voltage, v
4
2 toe-off(R) heel-off(L) toe-off(L) heel-off(R)
0
1 time, s intersection event
2 peak event
1 Mickelborough, J., Van der Linden, M.L., Tallis, R.C., and Ennons, A.R.: ‘Muscle activity during gait initiation in normal elderly people’, Gait Posture, 2004, 19, pp. 50–57 2 Pons, J.L.: ‘Wearable robots: biomechatronics exoskeletons’ (Wiley, Hoboken, NJ, USA, 2008), pp. 165–198 3 Kazerooni, H.: ‘Human power extender: an example of human–machine interaction via the transfer of power and information signal’. Proc. Int. Workshop Advanced Motion Control, Coimbra, Portugal, June 1998, pp. 565–572
Fig. 3 Insole-type FSR patterns of subjects There are two important particular events, such as vertical GRF events, that we can utilise to implement the precedence walking assistance mechanism without using biosignal
muscle force comparisons
100 50
heelstrike
toe-off
0
force, N
–50 –100 –150 –200
detection of step initiation
–250 –300
equipped not equipped
–350 –400
0
0.5
1.0 time, s
1.5
Fig. 4 Comparison results between operator equipped with UTRCEXO and operator not equipped with UTRCEXO
ELECTRONICS LETTERS 30th January 2014 Vol. 50 No. 3 pp. 146–148
