2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences I Langkawi I 17th - 19th December 2012
Design and Development of Wearable Automated Cerebral Palsy Measurement System Conceptual Development and Preliminary Findings
CHONG Yu Zheng
Jasmy Yunus
Department of Mechatronics and Biomedical Engineering Universiti Tunku Abdul Rahman Kuala Lumpur, MALAYSIA
[email protected]
Faculty of Health Science and Biomedical Engineering Universiti Teknologi Malaysia Skudai, Johor Bahru, MALAYSIA
Abstract-Assessment of Cerebral Palsy generally utilized 3-
assessments of cerebral palsy. Such gait laboratories are equipped primarily with video camera system, infrared optical system to perform 3 Dimensional Gait Analysis (3DGA), and electromyography (EMG) system to evaluate cerebral palsy [9][lO].
Dimensional Gait Analysis (3DGA) to determine gait deviations. Such analyses require dedicated laboratory setup which is not easily accessible, and portable. This project proposes a wearable system to provide such analysis without requiring a dedicated 3D gait laboratory and will enable analyses to be performed in daily life. The system composed of wireless wearable instrumentations
Setting up a 3DGA laboratory will require high initial funding. It is estimated that cost setting up such laboratory will cost more than €500,000 [6] (or RM1.94 million) [7]. As consequences, according to [8], the cost of 3DGA performed on individuals with cerebral palsy is high, and been identified as one of the major concerns by caretakers. Furthermore, 3DGA could only be performed in dedicated laboratory which poses inconveniences such as travelling to the laboratory to both patients and caretakers. In addition, 3DGA would not provide real-life assessment of individuals with cerebral palsy and in other words, analyses are confmed to static laboratory setting which might affect reliability of analyses been performed [11].
that are attached to the subject, and computer-based analysis system to provide real-time gait assessments. Preliminary results obtained by developed systems have shown promising outcomes for application in gait analysis.
Keywords- Cerebral Palsy, wearable system, Biomechanics, Gait Analysis, Biomechanicallnstrumentation
I.
INTRODUCTION
Cerebral palsy can be broadly defined as a neuro developmental condition that occurs in early childhood and is associated with a motor impairment [1]. There are various defmitions of cerebral palsy introduced in 1959[2], 1964[1], and 1994[3]. More recently, the new consensus definition defmed the following:"Cerebral palsy describes a group of disorders of the development of movement and posture, causing activity limitations that are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain. The motor disorders of cerebral palsy are often accompanied by disturbances of sensation, cogmtIOn, communication, perception, and/or behaviour, and/or by seizure disorder"[2].
Acknowledging such limiting factors, the project proposes development of full-body wearable, inexpensive system that consists of sensors, electronics, and computer-based analysis system as alternative to 3DGA. The development cost of the system is anticipated be around RM50,000. Therefore, with such minimal financial commitment, it is expected to benefit rehabilitation establishments to own such device to aid in improving the monitoring of children with cerebral palsy. It is anticipated that the system will provide comparable information of spatio-temporal, kinetics, and muscular activities of children with cerebral palsy comparable to more established systems such as the 3DGA that is commonly found in gait laboratories.
The number of incidence of cerebral palsy in developed nations such as United States, Western European Countries and Australia is between two and three cases per 1,000 live births or 0.2% and 0.3% [4]. In Malaysian context, registered cerebral palsy sufferers are 887 from estimated 47,044 in 2006 [5]. It have been estimated that the total number of disabled in Malaysia is 2 % of total population of Malaysia.
Since there are various assessment methods been introduced to assess different characteristics of motor functions and spasticity, the project propose an exploratory multimodal approach whereby combinations of Functional Motor Assessment Scale (FMAS), Gross Motor Function Measure (GMFM), Gross Motor Performance Measure (GMPM), and Motor Age Test (MAT) will be used to determine
Clinical biomechanical assessments have been one of the assessments for cerebral palsy. Most of industrialized countries have established gait laboratory to facilitate
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2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences I Langkawi I 17th - 19th December 2012
classifications of cerebral palsy of every individual [12]. This combination anticipated to provide a broad spectrum of assessment with quantitative nature, and with both evaluative, and discriminative nature. Therefore, it will be hypothesized that such combination will improve the reliability of assessments. II.
upper extremities whilst [14] for lower extremities. Nine (9) sensors will be attached to various anatomical landmarks of lower extremities on one side of the body. Measurements such as linear acceleration and angular acceleration (rotational motion) of various joints will be acquired by the IMUs. As such, kinetics parameters could be derived from the kinematics parameters measured by the sensors. Attachment of IMUs will be made by Velcro® straps, whereby each IMU units will be enclosed in an enclosure of 3 x 3 cm and affixed with Velcro® strap to be attached to various anatomical landmarks on both upper and lower extremities. The utilization of such attachment method will enable non obstructive of movements during gait assessment. Fig. 3 shows the anatomical landmarks proposed to be implemented in this project [13][14].
SYSTEM DEVELOPMENT
A. Overall System Overview
As outlined in the previous section, the proposed system consists of Upper Extremities Subsystem, and Lower Extremities Subsystem. The general architecture of the system consists of three different subsystems, namely, Wearable Sensor subystem, Wireless Data Transmission subsystem, and Computer-Based Data Acquisition subsystem. Fig. 1 shows the overview of subsystems.
Figure 1. Overview of Subsystems. B.
Wearable Sensor Subsystem
Fig. 2 shows the gait measurands identified for the wearable system. These include both kinematics and kinetics of gait which are acquired in 3DGA for analysis of cerebral palsy gait. Figure 3. Lower [14] and Upper [13] Extremities Sensor Attachment Sites Wearable Instrumentation Kinematics
The third subsystem is the wearable insole subsystem. This subsystem will be utilized to measure Vertical Ground Reaction Forces (VGRF) for ambulation. Differentiation between normal and pathological VGRF is essential in cerebral palsy whereby force platforms are utilized to measure these parameters in gait laboratory. The proposed wearable insole could replace the immovable force platforms whereby the latter could be inserted in any footwear. Each insole will be embedded with five FSRs (Interlink Electronics - 4 x 0.5" Circular FSRs, 1 x 1.5" Square FSR). Fig. 4 shows the arrangement of FSRs, and the first version prototype. The placement of FSRs are in accordance to well established arrangements in measuring peak forces, and based on the distributions of vertical ground reaction forces on the foot [20][21][22]. Fig. 4 also show the first completed prototype whereby all circuitries are placed in a pouch bag which enable the circuitry to be easily carried on the waist of test subject.
Kinetics
Figure 2. Wearable Instrumentation Systems with Measurands.
The proposed system will utilize 10 Three-Axes Inertial Measurement Unit (lMUs - ITG 3200/ADXL345) for upper extremities measurement system, 18 IMUs for lower extremities kinematics measurement, and 10 Force Sensing Resistors (FSRs - Interlink Electronics FSR) for development of shoe insole system. The IMUs will provide both linear and angular kinematics of upper and lower extremities joints which will be useful in determining the joint kinematics. Besides that, attachment sites of the wearable sensors are in accordance to [13] for
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2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences I Langkawi I 17th - 19th December 2012
D. Computer-based Data Analysis Subsystem
LabView® Student Version is proposed to be utilized to develop the Graphical User Interface, and real-time display of data from various sensor subsystems. The real-time data display will incorporates graphical display of data collected, storage of raw data collected from the subsystems. Besides that, post-processing of data would be incorporated to facilitate various post-data analysis to be performed which could aid in analyzing gait patterns and trends. Fig. 6 shows the graphical interface developed utilizing LabView Student Version.
Figure 4. The developed shoe insole with FSRs C.
Wireless Data Transmission System
Signal conditioning was done internally via in-board Analog-Digital Converter (ADC) embedded in the lMU, hence this will reduce the requirement of a separate ADC circuitry. In other words, the output of the sensor module is digitized.
Figure 6. The Preliminary User Interface Developed for Real-Time Datalogging and Graphical Display
As for the Insole subsystem, analog data collected by FSRs will be converted to Digital Signal through the onboard ADC incorporated in the microcontroller.
III.
Testing of the system was performed on thirty (30) normal test subjects of equal representation for each gender without any known gait deficiencies. Informed consents were obtained from each test subjects prior to data collections, and the data collection was approved by Ethical Committee. Table I shows the demographics of the test subjects.
Outputs of the sensor module will be fed to the microcontroller system for data collection and transmission. Arduino Uno R3 microcontroller was used in this development. X-Bee wireless communication module (SKXBee) was used to transmit data wirelessly. Fig. 5 depicts the wireless data transmission subsystem in overall system development.
Storage System
Circuitry, Filters,
Labview(r) Based
Amplifier
Datalogging
(Adruino
UNO)
Wireless Data Transmission Module (XBee)
TABLE I.
Data Analysis &
Sensors
Facility
r=-
PRELIMINARY TESTING
DEMOGRAPHICS OF TEST SUBJECTS
Gender
15 Females, 15 Males
Height (m)
1.60 (S.D. 0.05) Females 1.73 (S.D. 0.06) Males
Age (Years)
22.8 (S. D. 1.60)
Weight (N)
521 (S. D. 95) Females 701 (S. D. 127) Males
Every test subjects were required to walk normally under self selected speed along a flat flooring of 10 m in length with footwear. Three (3) trials were conducted on each test subject. This testing protocol is in accordance to [15][16][17]. For preliminary testing, test subjects are attached with lMUs on lower extremities, and shoe insole prior testing been conducted. The following section will discuss on the preliminary results generated by the developed subsystems.
XBee Wireless Receiver
Figure 5. Wireless Transmission Subsystem in the Proposed System
Relatively small form factors of the Arduino Uno microcontroller (7 cm x 5.3 cm) enabled the entire circuitry including data transmission module to be housed together in a small compact enclosure of 10 cm * 10 cm. Such physical characteristics are desirable in development of a wearable system which generally aimed to reduce intrusion and mobility to the test subject.
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2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences I Langkawi I 17th - 19th December 2012
IV.
TABLE III.
RESULTS AND DISCUSSION
As depicted in the previous section, data acquisition of the subsystems involved both Lower Extremities Kinematics, and the Vertical Ground Reaction Forces for walking. Table II shows the composite results generated by the Lower Extremities Subsystem Linear and Angular Motion for normal walking.
TABLE II.
Y-Axis Acceleration
Z-Axis Acceleration
Average (g)
-0.67
0.04
-0.72
Standard Deviation
0.27
0.15
0.90
Roll
Pitch
Yaw
Average e)
-1.47
-1.28
-0.26
Standard Deviation
3.70
0.69
0.43
VGRF
Male
Female
Average (BW)
1.00
2.18
Standard Deviation (SD)
0.67
1.15
Average VGRF recorded for normal walking are within 1.0 2.5 times of Body Weight which is reported in literatures [23] [24][25][26][27]. From the results obtained, it could be deduced that the average VGRF of male test subjects are lower compared to female subjects with a ratio 1:2.18. This may be due to the footwear habit of female samples in this testing whereby majorities are high heel footwear wearers [33]. Moreover, the VGRF will provide force and pressure distributions of the foot which is important in detecting any foot abnormalities in cerebral palsy [32]. Such parameters will provide gait stability assessments as one of the factors in the assessments.
LOWER EXTREMITIES ACCELERATIONS, AND JOINT ANGLES FOR NORMAL WALKING X-axis Acceleration
AVERAGE VERTICAL GROUND REACTION FORCE (VGRF) FOR MALE AND FEMALE SUBJECTS
Referring to both results obtained through the two subsystems namely the Lower Extremities Kinematics Measurement Subsystem, and the Instrumented Insole Subsystem shown the potential of the proposed system developed for utilization in detection of cerebral palsy to aid rehabilitation and long term monitoring without the needs for specialized dedicated laboratory. It is anticipated that a full body wearable instrumentation systems to quantify or detect movement disorders of the upper and lower extremities joints associated with cerebral palsy. Full body quantification of both kinematics and kinetics parameters are essential in distinguishing various gait patterns demonstrated by individuals with cerebral palsy.
As shown in Table II, results obtained are comparable with results obtained in [18] and [19] whereby the acceleration of trunk during normal walking is between -2 g to 2 g. Such acceleration data will be useful in determining joint linear and angular kinematics, and joint translations. Furthermore, these spatio-temporal parameters will be used to derive Joint Torques, Joint Moments, and Joint Forces which are necessity in Cerebral Palsy Gait Analysis [28][29][30][31]. The wearable insole system which is devised to obtain VGRF was tested, and Fig. 6 shows the average VGRF versus Time for Walking performed by the test subjects.
V.
Average VGRF versus Time for Walking z
1000
500
Future tasks identified are completion of the full-body instrumentation system with both upper and lower extremities measurements utilizing total of 38 IMUs, upgrading to two microcontrollers, to further validate the efficacy of the completed system, data collection from cerebral palsy test subjects, development of the automated analysis system that is capable of identifications of different sub-types of cerebral palsy, and finally rehabilitation, treatment plans, and long term monitoring of individuals with cerebral palsy.
o 0.0 00 0.2000 OAOOO 0.6000 0.8000 -500
Figure 6
1.0000
Average Time,s
-
CONCLUSION AND FUTURE WORKS
Generally, the proposed subsystem will utilize IMUs for joint kinematics measurements, while on the other hand, force sensing resistors are proposed to measure vertical ground reaction forces, and pressure profile of movement. Such arrangement will reduce the necessity of utilizing 3Dimensional Gait Analysis System.
Average VGRF versus Time Graph for Walking
It is anticipated that the developed systems could be one of the cost-effective, affordable, of good efficacy instrumented-based gait analysis system as alternative to the 3DGA systems.
Table III shows the Average VGRF for walking collected from test SUbjects.
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2012 IEEE EMBS International Conference on Biomedical Engineering and Sciences I Langkawi I 17th - 19th December 2012
[18] Kim, 1. W., & Park, C. (2004). A Step , Stride and Heading Determination for the Pedestrian Navigation System. Positioning, 1(8), 273-279.
ACKNOWLEDGMENT
The authors would like to record sincere appreciation to all test subjects who voluntarily participated in this study.
[19] Alahakone, A. U., & Senanayake, S. M. N. A. (2010). A Real-Time System With Assistive Feedback for Postural Control in Rehabilitation. IEEEIASME Transactions on Mechatronics, 15(2), 226-233. doi:I0.1109/TMECH.2010.2041030
REFERENCES [I]
Collins. P (2006).
[20] Pappas, I. P. \., Keller, T., Mangold, S., Popovic, M. R., Dietz, Y., & Morari, M. (2004). A Reliable Gyroscope-Based Gait-Phase Detection Sensor Embedded in a Shoe Insole. Sensors (Peterborough, NH), 4(2), 268-274.
Therapy and equipment needs of people with cerebral
palsy and like disabilities in Australia.
Canberra, ACT: Australian
Institute of Health and Welfare. [2]
Mac Keith RC, MacKenzie ICK & Polani PE 1959. The Little Club. Memorandum on terminology and classification of 'cerebral palsy'. Cerebral Palsy Bulletin 1(5): 27-35.
[3]
Mutch L, Alberman E, Hagberg B, Kodama K & Perat MY 1992. Cerebral palsy epidemiology: where are we now and where are we going? Developmental Medicine and Child Neurology 34(6):547-55.
[4]
[5]
[21] Liedtke, c., Fokkenrood, S. A. W., Menger, 1. T., Kooij, H. Y. D., & Yeltink, P. H. (2007). Evaluation of instrumented shoes for ambulatory assessment of ground reaction forces. Gait & Posture, 26, 39-47. doi:I0.1016/j.gaitpost.2006.07.017 [22] Bamberg, S. J. M., Benbasat, A. Y., Scarborough, D. M., Krebs, D. E., & Paradiso, J. A. (2008). Gait analysis using a shoe-integrated wireless sensor system. IEEE transactions on information technology in
Kamaruddin, K. (2007). Adult Learning for People with Disabilities in Malaysia : Provisions and Services. The Journal of Human Resource and Adult Learning, 3(2), 50-64.
biomedicine: a publication of the iEEE Engineering in Medicine and Biology SOCiety,
Honeycutt A, D. L., Chen IT, al Homsi G. (2004). "Economic costs associated with mental retardation, cerebral palsy, hearing loss and visual impairment." MMWR Weekly 53(03): 57 - 59.
[6]
http://www.crc.ie/services gai.shtml, Retrieved on 13/07/2012.
[7]
http://themoneyconverter.com/EURIMYR.aspx, 1310712012.
[8]
Collins, P (2006).
Retrieved
[24] Gouwanda, D., & Senanayake, S. M. N. A. (2008). Real Time Multi Sensory Force Sensing Mat for Sports Biomechanics and Human Gait Analysis. Computer Systems Science and Engineering.
on
Therapy and eqUipment needs of people with cerebral
palsy and like disabilities in Australia.
[25] Liedtke, c., Fokkenrood, S. A. W., Menger, J. T., Kooij, H. Y. D., & Yeltink, P. H. (2007b). Evaluation of instrumented shoes for ambulatory assessment of ground reaction forces. Gait & Posture, 26, 39-47. doi:10.1016/j.gaitpost.2006.07.017
Canberra, ACT: Australian
Institute of Health and Welfare. [9]
12(4), 413-23. doi:l0.1109ITITB.2007.899493
[23] Riley, P. O., Paolini, G., Della Croce, U., Paylo, K. W., & Kerrigan, D. C. (2007). A kinematic and kinetic comparison of overground and treadmill walking in healthy SUbjects. Gait & posture, 26(1), 17-24. doi:10.1016/j.gaitpost.2006.07.003
Molloy, M., McDowell, B. c., Kerr, c., & Cosgrove, a P. (2010). Further evidence of validity of the Gait Deviation Index. Gait & posture, 31(4), 479-82. Elsevier B.Y. doi: 10.1016/j.gaitpost.2010.01.025.
[26] Senanayake, S. M. N., Zeng, C., Shen, c., Chong, 1., & Sirisinghe, R. (2006). Instrumented Orthopaedics Analysis System. 2006 iEEE International Conference on Automation Science and Engineering, 194199. Ieee. doi:I0.1109/COASE.2006.326879
[10] Lauer, R. T., Stackhouse, C., Shewokis, P. a, Smith, B. T., Orlin, M., & McCarthy, J. J. (2005). Assessment of wavelet analysis of gait in children with typical development and cerebral palsy. Journal of biomechanics, 38(6), 1351-7. doi: 10.1016/j.jbiomech.2004.07.002.
[27] Fernery, Y., Moretto, P., Renaut, H., Th6venon, A., & Lensel, G. (2002). Measurement of plantar pressure distribution in hemiplegic children: changes to adaptative gait patterns in accordance with deficiency. Clinical biomechanics (Bristol, Avon), 17(5), 406-13. Retrieved from http://www.ncbi.nlm.nih.gov/pubmedlI2084546
[11] Heinze, F., Hesels, K., Breitbach-Faller, N., Schmitz-Rode, T., & Disselhorst-Klug, C. (2010). Movement analysis by accelerometry of newborns and infants for the early detection of movement disorders due to infantile cerebral palsy. Medical & biological engineering & computing, 48(8), 765-72. doi: 10.1007/s115I7-010-0624-z.
[28] Romei, M., Galli, M., Motta, F., Schwartz, M., & Crivellini, M. (2004). Use of the normalcy index for the evaluation of gait pathology, 19, 8590. doi:I0.1016/S0966-6362(03)00017-1
[12] Ketelaar, M., Yermeer, A., & Helders, P. 1. (1998). Functional motor abilities of children with cerebral palsy: a systematic literature review of assessment measures. Clinical rehabilitation, 12(5), 369-80. doi: 10.11911026921598673571117. [13] Kavanagh, 1. J., & Menz, H. B. (2008). Accelerometry : A technique for quantifying movement patterns during walking. Gait & Posture, 28(1), I-IS. doi:I0.1016/j.gaitpost.2007.I0.010
[29] Kim, K. S., Seo, J. H., & Song, C. G. (2011). Portable measurement system for the objective evaluation of the spasticity of hemiplegic patients based on the tonic stretch reflex threshold. Medical engineering & physics, 33(1), 62-9. Institute of Physics and Engineering in Medicine. doi:I0.1016/j.medengphy.2010.09.002
[14] Rueterbories, 1., Spaich, E. G., Larsen, B., & Andersen, O. K. (2010). Methods for gait event detection and analysis in ambulatory systems. Medical engineering & physics, 32(6), 545-552. Institute of Physics and Engineering in Medicine. doi:10.1016/j.medengphy.2010.03.007
[30] Carriero, A., Zavatsky, A., Stebbins, J., Theologis, T., & Shefelbine, S. J. (2009). Determination of gait patterns in children with spastic diplegic cerebral palsy using principal components. Gait & posture, 29(1), 71-5. doi:lO.1016/j.gaitpost.2008.06.0II
[15] Latour, E., Latour, M., Arlet, 1., Adach, Z., & Bohatyrewicz, A. (2011). Gait functional assessment: Spatio-temporal analysis and classification of barefoot plantar pressure in a group of 11-12-year-old children. Gait & posture, 34(3), 415-20. Elsevier B.Y. doi:10.1016/j.gaitpost.2011.06.013
[31] McConnell, K., Johnston, L., & Kerr, C. (2011). Upper limb function and deformity in cerebral palsy: a review of classification systems. Developmental medicine and child neurology, 53(9), 799-805. doi:10.llllIj.1469-8749.2011.03953.x [32] Tomizuka, M. (2009). A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe. IEEEIASME Transactions on Mechatronics, 14(3), 358-370. doi:10.1109/TMECH.2008.2008803
[16] Schwesig, R., Leuchte, S., Fischer, D., Ullmann, R., & Kluttig, A. (20II). Inertial sensor based reference gait data for healthy SUbjects. Gait & posture, 33(4), 673-8. doi:I0.1016/j.gaitpost.2011.02.023
[33] Shaban, H. A., Abou el-Nasr, M., & Buehrer, R. M. (2010). Toward a highly accurate ambulatory system for clinical gait analysis via UWB radios. iEEE transactions on information technology in biomedicine: a
[17] Williams, S. E., Gibbs, S., Meadows, C. B., & Abboud, R. 1. (2011). Gait & Posture Classification of the reduced vertical component of the ground reaction force in late stance in cerebral palsy gait. Gait & Posture, 34(3), 370-373. Elsevier B.Y. doi:I0.1016/j.gaitpost.2011.06.003
publication of the IEEE Engineering in Medicine and Biology Society,
14(2), 284-91. doi:10.1109ITITB.2009.2037619
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