Development of a Pressure Control System for Brace ... - IEEE Xplore

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 20, NO. 4, JULY 2012

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Development of a Pressure Control System for Brace Treatment of Scoliosis Eric Chalmers, Edmond Lou, Doug Hill, Vicky H. Zhao, and Man-Sang Wong

Abstract—Bracing is a common nonsurgical treatment for scoliosis, but its effectiveness has been debated. Some clinical studies have shown efficacy of brace treatment is correlated to how the brace has been worn. The more often the patients wear their braces to the prescribed tightness as well as the prescribed length of wear each day, the better the treatment outcome. A system of four wireless pressure control devices was developed to understand brace wear-time and regulate a target pressure range at the brace–body interface. Each pressure control device could function independently and be embedded in the brace at key pressure areas. Such a system could improve the quality of brace wear—making the treatment more effective and refining our understanding of the three-pressure-point brace treatment concept during daily activities. This paper reports the system development and validation. The system was tested on four healthy subjects for 2 h without pressure regulation and 2 h with regulation. The results show that the pressure regulation doubled the time spent in a desired pressure range on average (from 31% to 62%). Brace-wear time was logged correctly. The system was also validated through a seven-day continuous test, and a fully charged battery could run for 30 days without requiring recharge. Index Terms—Assistive technology, scoliosis, smart orthotic management, wearable computer.

I. INTRODUCTION

A

DOLESCENT idiopathic scoliosis (AIS) is a deformation of the spine involving lateral curvature and vertebral rotation. It affects 1.5%–3% of the population [1]. Scoliotic patients usually function at or near normal levels but have increased pain prevalence and sometimes increased pain severity, lower self-image, and can have lower social function compared to the general population [2]. An AIS patient’s spinal curve can progress during periods of rapid growth. A curve which is allowed to progress during adolescence can continue to progress afterward, potentially requiring corrective surgery [3]. Spinal specialists try to avoid surgery by prescribing a custom-made rigid brace to prevent

Manuscript received September 16, 2011; revised February 05, 2012; accepted March 15, 2012. Date of publication April 13, 2012; date of current version July 03, 2012. This work was supported by the Natural Sciences and Engineering Research Council (NSERC) and the Northern Alberta Benefit Society for Scoliosis. E. Chalmers and V. H. Zhao are with the Electrical and Computer Engineering Department, University of Alberta, Edmonton, AB, T6G 2V4 Canada. E. Lou is with the Electrical and Computer Engineering Department, University of Alberta, Edmonton, AB, T6G 2V4 Canada, and also with Research and Technology Development, Glenrose Hospital site, Alberta Health Services Edmonton, AB, T5G 0B7 Canada (e-mail: [email protected]). D. Hill is with Alberta Health Services Edmonton, AB, T5G 0B7 Canada. M.-S. Wong is with Health Technology and Informatics Department, The Hong Kong Polytechnic University, Hong Kong. Digital Object Identifier 10.1109/TNSRE.2012.2192483

curve progression. Brace treatment is generally considered successful when curve progression is kept below 5 until skeletal maturity [4]. Braces are padded to apply corrective pressure to the torso using a three-point concept [5]: one pad is placed such that it will exert a force just below the spinal curve’s apex. Two counter-pressure pads are placed opposite, above and below the curve. Thus, three pads are used for a single curve, and four for a double curve. Orthotists (who design and build braces) rely on experience to shape a place pads to exert an appropriate level of corrective pressure when the brace is tightened. This pressure is chosen with consideration of such factors as patient body mass, age, and gender. There is currently no standard for an ideal level of brace pressure, so the orthotist’s intuition and judgment are trusted. The brace is prescribed along with a treatment protocol, indicating the expected tightness and daily duration of brace wear. Correlations have been found between brace tightness and success [6]–[8], so patients are often asked to don their brace as tightly as is tolerable. Brace wear-time has also been shown to influence success [2], [5], and prescriptions vary from 8 h per day to full-time (20 h per day or more), depending on the brace used and the particular case [5]. The effectiveness of bracing has been controversial [9], with some studies finding it highly successful [2], [10] and other studies asserting it is ineffective [11]–[13]. Two major problems contribute to this confusion: The amount of pressure exerted by the brace is unknown, and the duration of brace wear is unknown. Without controlled (or at least known) pressure and wear-time, no meaningful conclusions about brace effectiveness can be drawn. Technology has been applied to address these problems. Temperature sensors [10], [14], [15] pressure switches [16], and force sensors [17], [18] have been used to monitor brace pressure and/or wear-time. Approaches like these have shown that actual brace wear-time is usually lower than that reported by the patient themselves [14], [15], [19]. More alarming though, they have shown that brace pressure varies dramatically with patient activity and posture [20], and that it decreases gradually over time even though wear-time increases [21], [22]. Thus, even a faithfully compliant patient may not receive the optimum effectiveness of the brace treatment during the periods between orthotist inspections. What is needed is a system to not only monitor pressure and wear-time but also regulate brace pressure long-term. This system would improve the effectiveness of existing braces by creating consistent corrective pressure. The system must be reliable and acceptable to the patient. In 2005, Lou et al. [23] developed a device to monitor and regulate brace pressure, but

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Fig. 2. Flow diagram showing operation of pressure monitor/regulator unit.

Fig. 1. Monitor-regulator unit and its intended placement.

the device was large, required frequent recharging, and had limited functionality. Thus effectiveness and patient acceptance were limited. This paper reports on the development of a system which regulates brace pressure in accordance with the three-point concept while presenting minimal inconvenience to the patient. This study shows that a brace pressure regulation system can be practically and effectively implemented. II. METHODS A. System for Regulating Brace Pressure A spinal brace is made of polypropylene material, generally padded with medium-density foam, and often custom-made to fit for each patient’s size, deformity and goals of treatment [5]. Given that a brace for a double curve would use four pressure pads, our system entailed four pressure monitor-regulator units. Each unit consisted of: 1) an inflatable air bladder to apply pressure to the body; 2) an electronic pump and valve to control bladder air pressure, housed in an enclosure measuring 6 4.5 2.5 cm; 3) a pressure sensor; and 4) an electronic controller measuring 5.5 3.5 1.5 cm. Each inflatable bladder could be used as a pressure pad inside the brace and the air pressure adjusted to regulate brace pressure at that location. The controller unit and pneumatics had a combined mass of 110 g. 1) Air Bladder and Pneumatics: Infant blood pressure cuffs were used as inflatable air bladders (Critikon, Tampa, FL, size 4). A small 5-V electric diaphragm pump rated to 50 kPa (Sensidyne, Mülheim, Germany) and an electric solenoid valve rated to 43 kPa (Electrodyne, Batavia, OH) were used to inflate and deflate the bladder. Pneumatic components were chosen based on a maximum expected pressure of 16 kPa [7]. To inflate the bladder, the pump was activated and the valve opened to allow air flow into the bladder. The bladder was deflated by opening the valve, allowing air to escape through a small hole placed in the line between the pump and valve (see Fig. 1). 2) Pressure Sensor: Pressure sensing used the 1451-005G-T piezoresistive gauge pressure sensor (Measurement Specialties,

Hampton, VA), which consists of four elements in a full Wheatstone bridge configuration for a small temperature coefficient (0.13%/ C). An instrumentation amplifier (with gain of 55) created a voltage proportional to pressure. 3) Electronic Controller: The key component of each electronic controller was the CC2530 system-on-chip (Texas Instruments, Dallas, TX), which features an 8051 processor, an IEEE 802.15.4 radio transceiver, and a sigma-delta analog to digital converter (11 bits effective resolution) used to monitor battery voltage and read pressure. Other components of the controller unit included the M41T93ZQA6F real-time clock (ST Microelectronics, Geneva, Switzerland) for timekeeping, the M25P32 (Numonyx, USA) 4 MB flash memory for logging data, and the TPS61240 boost converter (Texas Instruments, Dallas, TX) to generate a 5-V supply from the 3.7 V 900 mA h lithium polymer battery. 4) Unit Operation: The monitor-regulator unit logged average pressure applied to the body and kept the average pressure within a range recommended by the orthotist or clinician. Once the units were installed in a brace, user interface software was used to set up each unit for long-term operation. This setup included specifying desired pressures and tolerances. Fig. 2 shows a simplified flow diagram of the normal operating mode. Each minute, eight pressure samples were taken over 2 s and averaged. This helped reduce the effect of breathing in the measurement. Our tests showed that without this step, aliased breathing measurements could cause up to 25% error in pressure magnitude over an averaged 8-min pressure reading period. The average of these eight samples was passed through a feedback network consisting of an exponential average . The feedback network output was compared to the clinician-specified desired pressure and was maintained within a specified tolerance by inflating or deflating the air bladder. The feedback network’s effect was similar to an 8-min moving average; as a result the system would not respond to brief impulses in the bladder pressure. A breathing detection algorithm was developed to detect brace-wear compliance. (Simply detecting bladder pressure was insufficient for this purpose, as the bladder could be inflated to the target pressure with or without the patient present.) The breathing detection algorithm calculated the range of the eight pressure samples taken each minute; a range greater than 80 N/m in these samples meant that the patient’s breathing was detected and the brace was being worn (compliance). The detection scheme included some hysteresis: the compliance state would only switch from “true” to “false” if four out of

CHALMERS et al.: DEVELOPMENT OF PRESSURE CONTROL SYSTEM FOR BRACE TREATMENT OF SCOLIOSIS

the last five compliance readings were “false,” and would only switch from “false” to “true” if four out of five readings were “true”. This improved reliability of the compliance measure at the expense of introducing a 4–5 min delay (offset) in detected compliance. A brace is typically worn for several hours, so this offset will not materially affect the compliance score. Each of the three or four pressure sites was used to determine compliance. The brace was deemed to be in the ON state when any of the sites detected that the brace was worn. During bladder inflation/deflation the sampling rate changed to a constant 4 Hz and the integrator was bypassed so the control logic could quickly respond to the near instantaneous pressure alterations. Once instantaneous pressure was within the set tolerance range a new 8-sample average pressure was obtained and, if necessary, additional pressure adjustments were made. Otherwise the normal 8-samples-each-minute scheme was resumed with the unit entering a low power mode between samples. Pressure was logged minutely in 8-byte packets including timestamps, with capacity to store up to one year of samples in the 4 MB memory. Pump and valve operation were suspended at night (start and stop times were adjustable during setup) to avoid waking the patient. Previous work in our laboratory showed that brace pressure was less variable during the night as well [8], suggesting that pressure adjustment was not needed as much as during the day. To keep timing consistent between units, the unit assigned as number “1” broadcast its clock time to the others for 30 s every 6 h. 5) User Interface Software: Pressure control units communicated with a PC through an IEEE 802.15.4 radio dongle (Adaptive Modules, Sussex, U.K.). Custom software was developed in Microsoft Visual C# to communicate through the dongle with four pressure regulation units simultaneously. The software displayed real-time data from each unit, allowed adjustment of operating parameters, downloaded logged data, and allowed calibration of sensors. The calibration involved measuring the sensor’s zero-pressure offset; a specific experimentally determined scale factor was used for each sensor. Each unit stored its own operating parameters, so the radio link with the PC was only necessary for initial setup and for downloading data. 6) Safety Features: The software user interface required the user to enable pressure regulation each time the clinician-specified pressure settings were changed. This prevented pressure regulation from being enabled by accident. In the event of a sensor failure, the unit may incorrectly determine that no pressure is applied and continue to inflate the bladder to potentially harmful levels. A safety timeout prevented this situation by draining the bladder and shutting the unit down if the pump ran for more than 13 s continuously (the maximum expected time to inflate the bladder to the highest peak therapeutic level of 16 kPa) [7]. Furthermore, on power-up the valve was opened for 2 s to release pressure in the bladder. Thus, toggling the unit’s power would allow pressure to be relieved if necessary. B. Laboratory Tests 1) Pressure Sensor Accuracy: The 1451-005G-T pressure sensors were tested for linearity, hysteresis, and time-invari-

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Fig. 3. Brace worn for testing purposes, fitted with three pressure regulation units. Two units are visible; the third is over the patient’s chest.

ance. To compare linearity between sensors, the bladder was inflated to 16 kPa (as measured by a mechanical manometer) and readings from four different sensors taken at multiples of 1.3 kPa as it deflated to 2.7 kPa. The linear regression of each sensor was calculated. The slopes of each line were also compared in order to justify the practice of using a common scale factor in calibrating the sensors. Sensor output was tested during loading and unloading to confirm the manufacturer’s claim of low hysteresis. An air bladder was inflated to 16 kPa and then deflated to 4 kPa three times in sequence. One inflation and deflation took about 40 s. A sensor measured the bladder pressure during this activity, and the analog to digital converter readings of the sensor’s output were recorded at 4, 5.3, 8, 10.7, 13.3, and 16 kPa. The readings for the three inflations and three deflations were averaged. A brief test of time invariance was conducted by taking sensor readings at 5.3, 10.7, and 16 kPa, on days 1, 2, and 5 of a five-day test. The variation in the readings was measured. 2) Effectiveness of Pressure Regulation Algorithm: To test the system’s effectiveness in controlling brace pressure, four test subjects (nonscoliotic males ages 17–25) wore a custom made brace fitted with three units (see Fig. 3). The test protocol received ethics approval from the local ethics board. The units were randomly placed, as placement was irrelevant for validation purposes. The brace was worn for two periods of 2 h each—one with pressure regulation disabled and one with regulation enabled. In both cases pressure was set to 5.3 kPa before beginning the test, as this was a substantial but still comfortable pressure for our subjects. Tolerance was set to 0.67 kPa ( 13% of the target pressure—a somewhat smaller tolerance than that used by Lou [23]) for the pressure-regulated tests. Logged data were analyzed after each test; the proportion of 8-min-average pressure readings falling within the 5.3 0.67 kPa target range was recorded, as well as the overall average pressure. For the purpose of the test, the number of inflations/deflations was also recorded. Comparing the regulation disabled and enabled tests shows the improvement of the system over conventional bracing, in terms of pressure consistency.

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The placement of the units in the brace remained constant throughout all testing, and the subjects tried to perform similar activities in both the regulated and unregulated tests. These activities included sitting at a desk, standing for at least 5 min at a time, and walking for 5–15 min. The range of activities was intended to simulate the range of postures encountered during daily activity. 3) Reliability of Compliance Monitoring Feature: A subject wore a brace fitted with two randomly placed units for 1 h while performing activities including sitting, standing, and walking. Pressure was set to 1.3 1.3 kPa so that the pressure could at times drop to zero (i.e., the bladder could lose contact with the subject’s body). Since compliance monitoring relied on pressure variations caused by breathing, the intent was to find the minimum bladder pressure at which these variations could be detected. After the test each unit’s compliance readings were analyzed along with its pressure readings to estimate the minimum bladder pressure at which the compliance monitoring feature could function. 4) Battery Life and Long-Term Validation: Battery life is an important metric, as the need for frequent recharging deters user acceptance. Power consumption was tested by setting the unit to maintain 8 kPa and recording average current drawn over 1 h. The air bladder was completely deflated four times during the hour, forcing the unit to reinflate it. The intent was to simulate an hour of typical usage with several pump/valve activations. Nighttime consumption was tested by measuring average current over 15 min with pressure regulation disabled. General long-term function was tested by setting a unit to maintain 8 0.5 kPa for one week. During this test the unit was placed on a desktop and the air bladder loaded with a 100 g mass to increase the rate of air leakage. After and during the test, logged data were downloaded to verify that samples were logged each minute, bladder pressure was maintained during the day, pressure regulation was disabled at night (9:00 pm to 8:00 am), and battery voltage was not lower than expected after one week of operation. Wireless communication was tested by downloading 1700 logged samples three times at a range of 4 m (the size of a typical examination room) and measuring the number of packets lost. III. RESULTS A. Pressure Sensor Accuracy Fig. 4 shows highly linear outputs from each sensor. Each sensor had a unique offset and slope (gain). The offset of each sensor was accounted for during calibration, and all slopes were within 6% of the average slope. This 6% corresponded to 0.48 kPa maximum error over an 8 kPa range (4–8 kPa are the most commonly experienced brace pressures [7]) when using the average slope to interpret all sensor outputs. Thus, using a common scale factor to read all sensors contributed 0.48 kPa error over the expected pressure range. For more demanding application a two-point calibration scheme could be adopted, measuring both the sensor’s offset and gain. Fig. 5 shows nearly identical sensor outputs during loading (inflation) and unloading (deflation). This indicates that the sensor is essentially hysteresis free.

Fig. 4. Results of pressure sensor linearity testing. Each sensor shows a unique offset, but all are linear and slopes are within 6% of the average slope. Analog to digital converter is 12 bit with a full scale voltage of 3.3 V.

Fig. 5. Sensor response to loading/unloading. Nearly identical inflation/deflation responses indicate no significant hysteresis. Analog to digital converter is 12 bit with a full scale voltage of 3.3 V.

The time-invariance test showed a maximum variation in sensor output of 1.25%, suggesting good repeatability of the measurements. B. Effectiveness of Pressure Regulation Algorithm Fig. 6 shows percentages of each subject’s pressure readings falling below, in, and above the target range of 5.3 0.67 kPa. Enabling pressure regulation increased the percentage of time spent in the target range for all four subjects; on average the readings were in-range twice as often (increasing from 31% to 62%). The time spent below-range was reduced (from 45% to 12% on average) but time spent above-range was relatively unchanged (a slight increase from 24% to 26%). Between the three monitor-regulator units, bladder inflations/deflations occurred 40, 33, 35, and 59 times over the 2-h test for subjects A through D, respectively. Fig. 7 shows the pressure readings from one monitor-regulator unit worn by subject A. These readings show the wide range of pressures experienced without regulation, due to the changes in patient posture. In contrast, the regulated pressure readings were kept in a much narrower range. Bladder inflation occurred each time pressure dropped below 4.63 kPa in the regulated test. For example, these inflations can be seen in Fig. 7 at 7 min, 20 min, and 1 h 43 min into the test. Similarly, the bladder was deflated when pressure rose above 5.97 kPa at 33 min, 55


Fig. 6. Percentage of readings falling below, in, and above target range with and without pressure regulation. Proportion of pressure readings falling below, in, and above the target range are shown for each subject. Time spent in the target range is significantly improved when using the regulating system.

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Fig. 8. Pressure readings from long term validation test, with pressure regulated to 8 0.5 kPa. Monitor-regulator compensates for leakage during the day (8:00 am to 9:00 pm) and suspends operation during the night.

D. Battery Life and Long-Term Validation

Fig. 7. Pressure readings collected from one monitor-regulator unit for subject A. Improved consistency in pressure when regulation is enabled can be seen.

min, and 1 h 20 min. The periods of time spent above the 5.97 kPa threshold showed that the monitor-regulator was unable to drain the bladder fast enough to achieve an immediate decrease in pressure (they did not indicate a failure of the algorithm itself). This also explains the lack of change in above-range readings in Fig. 6. The test subjects reported that pressure regulation did not make wearing the brace less comfortable or limit their ability to perform activities. C. Reliability of Compliance Monitoring Feature Pressure applied by the brace is not uniform, with some areas intended to be reliefs and some sites to have concentrated loads. Each sensor detected pressure at specific sites. The first unit experienced an average pressure of 0.24 0.45 kPa and erroneously recorded noncompliance for 52% of the hour. The second unit experienced an average pressure of 0.75 0.41 kPa and correctly recorded compliance for the full hour. A qualitative analysis showed that when pressure trended below 0.27 kPa, the compliance monitoring feature failed. For pressures above 0.27 kPa, compliance was detected perfectly except for a 2–4-min delay caused by the hysteresis in the detection algorithm.

The average current drawn from a 3.7-V source with pressure regulation enabled was 1.5 mA. Current drawn with regulation disabled was 0.05 mA. After derating the 900 mA h battery to a conservative capacity of 750 mA h, and assuming regulation would be disabled for 8 h each night, battery life was calculated to be 1 month (750 mA h/[1.5 mA 16 h/day 0.05 mA 8 h/day] 30.7 days). Fig. 8 shows logged pressure readings from the long-term functionality test which showed that pressure and compliance samples were logged appropriately each minute, the bladder was reinflated each time leakage caused its pressure to drop below 7.5 kPa, and these reinflations stopped during the night. During this test logged data were randomly downloaded once each day to confirm proper operation. This involved moving and replacing the unit on the desktop each day, and the change in position caused variations in the rate of air leakage. These slight variations can be seen from day to day in Fig. 8, especially between days 3 and 4. The final battery voltage was 4.11 V, showing most of the battery’s capacity was unused. With no clock synchronizations, the device’s clock time had drifted only 10 s with respect to a computer clock over the week, corresponding to less than 1-s drift over the 6-h synchronization period used. The wireless communication range test showed no packet loss at four meters. IV. DISCUSSION Although bracing is a commonly prescribed nonsurgical treatment for AIS, its effectiveness is controversial. This may be because the compliance with prescribed wear-time and the pressure at which the brace is worn are highly variable. If a patient is wearing the brace infrequently and/or not tightening the straps to the prescribed level, the brace is not affecting their scoliosis. Wear-time is determined solely by the patient’s willingness to wear the brace, but this system can improve the pressure applied by the brace while it is worn, potentially resulting in better treatment outcomes. The system includes up to four pressure regulating units for installation at the brace’s main pressure points (the software could be expanded to accommodate a system of dozens of units). The four units are self-contained and wireless, allowing easy installation of each unit into cavities in the brace without burdensome wiring harnesses. Monitoring pressure with pressure

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sensors instead of force sensors is advantageous as the orientation of the sensor need not be considered. Initial performance tests show an improvement in brace pressure over the conventional, uninstrumented brace. The system reduced the variability of pressure and doubled the time spent in the target range. The system improved in-range time by reducing the amount of below-range time, while above-range time was relatively unchanged. Enlarging the hole between the pump and valve would allow the unit to drain the bladder faster (at the expense of less efficiency in inflating the bladder) and improve its ability to reduce above-range time. The system monitors brace wear compliance reliably for a typical therapeutic range [7] of brace pressure. The full benefit of this system is not only its ability to maintain a desired pressure, but also the effect it has on the patient’s interaction with their brace. In a conventional brace the patient can pull away from the pressure pads (by straightening their spine) to reduce the force on their torso. This creates an active correction mechanism in addition to the brace’s passive support. With this system however, when the patient straightens the monitor-regulator will restore the original pressure, prompting the patient to straighten further. In this way, the active correction mechanism may be facilitated and enhanced by the system. This benefit will need to be proven in clinical studies. Do improvements in brace pressure mean that treatment outcome could be improved for the same wear-time? Or that weartime could be reduced without affecting outcome? It is hoped that this system will help answer these questions, improve brace effectiveness, and provide understanding of the relationship between brace effectiveness and brace wear quantity and quality. V. CONCLUSION A system was developed which regulates brace pressure to a specified level. The proportion of time spent in a target pressure range was twice as high using the system, as it was using only the conventional brace. The system’s size and efficiency will allow a brace to be practically instrumented. Regulated pressure should improve brace effectiveness. REFERENCES [1] J. Lonstein, “Adolescent idiopathic scoliosis,” Lancet, vol. 344, no. 8934, p. 1407, 1994. [2] M. Asher and D. Burton, “Adolescent idiopathic scoliosis: Natural history and long term treatment effects,” Scoliosis, vol. 1, pp. 2–10, 2006. [3] S. L. Weinstein and I. V. Ponseti, “Curve progression in idiopathic scoliosis,” J. Bone Joint Surg., vol. 65, pp. 447–455, 1983. [4] S. Negrini et al., “Braces for idiopathic scoliosis in adolescents,” Spine, vol. 35, no. 13, pp. 1285–1293, 2010. [5] Manual of brace treatment for idiopathic scoliosis [Online]. Available: http://www.srs.org/professionals/education_materials/SRS_bracing_manual/ 2009 [6] J. Clin, C. Aubin, S. Parent, A. Sangole, and H. Labelle, “Comparison of the biomechanical 3D efficiency of different brace designs for the treatment of scoliosis using a finite element model,” Eur. Spine J., vol. 19, no. 7, pp. 1169–1178, 2010. [7] H. Jiang, V. J. Raso, D. Hill, N. Durdle, and M. Moreau, “Interface pressures in the Boston brace treatment for scoliosis,” in Proc. Int. Symp. 3-D Scoliotic Deformities, Montreal, Canada, Jun. 27–30, 1992, pp. 395–399. [8] E. Lou, V. J. Raso, D. Hill, J. Mahood, and M. Moreau, “Correlation between quantity and quality of orthosis wear and treatment outcomes in adolescent idiopathic scoliosis,” Prosthetics Orthotics Int., vol. 28, no. 1, pp. 49–54, 2004.

[9] L. Dolan, M. Donnelly, K. Spratt, and S. Weinstein, “Professional opinion concerning the effectiveness of bracing relative to observation in adolescent idiopathic scoliosis,” J. Pediatric Orthopedics, vol. 27, no. 3, pp. 270–276, 2007. [10] D. Katz, A. Herring, R. Browne, D. Kelly, and J. Birch, “Brace wear control of curve progression in adolescent idiopathic scoliosis,” J. Bone Joint Surg., vol. 92-A, no. 6, pp. 1343–1352, 2010. [11] C. Goldberg, D. Moore, E. Fogarty, and F. Dowling, “Adolescent idiopathic scoliosis: The effect of brace treatment on the incidence of surgery,” Spine, vol. 26, no. 1, pp. 42–47, 2001. [12] C. Goldberg, F. Dowling, J. Hall, and J. Emans, “A statistical comparison between natural history of idiopathic scoliosis and brace treatment in skeletally immature adolescent girls,” Spine, vol. 18, pp. 902–908, 1993. [13] L. Karol, “Effectiveness of bracing in male patients with idiopathic scoliosis,” Spine, vol. 26, no. 18, pp. 2001–2005, 2001. [14] G. Nicholson, M. Ferguson-Pell, K. Smith, M. Mchir, and T. Morley, “The objective measurement of spinal orthosis use for the treatment of adolescent idiopathic scoliosis,” Spine, vol. 28, no. 19, pp. 2243–2251, 2003. [15] M. Takemitsu, J. Bowen, T. Rahman, J. Glutting, and C. Scott, “Compliance monitoring of brace treatment for patients with idiopathic scoliosis,” Spine, vol. 29, no. 18, pp. 2070–2074, 2004. [16] R. Havey et al., “A reliable and accurate method for measuring orthosis wearing time,” Spine, vol. 27, no. 2, pp. 211–214, 2002. [17] J. Mac-Thiong, Y. Petit, C. Aubin, S. Delorme, J. Dansereau, and H. Labelle, “Biomechanical evaluation of the Boston brace system for the treatment of adolescent idiopathic scoliosis: Relationship between strap tension and brace interface forces,” Spine, vol. 29, no. 1, pp. 26–32, 2004. [18] E. Lou, D. Hill, and J. Raso, “A wireless sensor network system to determine biomechanics of spinal braces during daily living,” Med. Biol. Eng. Comput., vol. 48, no. 3, pp. 235–243, 2010. [19] S. Vandal, C. Rivard, and R. Bradet, “Measuring the compliance behavior of adolescents wearing orthopedic braces,” Issues Comprehensive Pediatric Nurs., vol. 22, no. 2–3, pp. 59–73, 1999. [20] C. Aubin et al., “Variability of strap tension in brace treatment for adolescent idiopathic scoliosis,” Spine, vol. 24, no. 4, pp. 349–354, 1999. [21] E. Lou, D. Hill, D. Hedden, M. Moreau, J. Mahood, and J. Raso, “An objective measurement of brace usage for the treatment of adolescent idiopathic scoliosis,” Med. Phys. Eng., vol. 33, pp. 290–294, 2011. [22] I. Mak et al., “The effect of time on qualitative compliance in brace treatment for AIS,” Prosthetics Orthotics Int., vol. 32, no. 2, pp. 136–144, 2008. [23] E. Lou, D. Hill, J. Raso, M. Moreau, and J. Mahood, “Smart orthosis for the treatment of adolescent idiopathic scoliosis,” Med. Biol. Eng. Comput., vol. 43, no. 6, pp. 746–750, 2005.

Eric Chalmers received the B.Sc. degree in electrical engineering, in 2011, from the University of Alberta, Edmonton, AB, Canada, where he is currently pursuing the Ph.D. degree in biomedical/electrical engineering. His research interests include nonsurgical treatment of scoliosis and the application of electronics engineering and machine learning to biomedical problems.

Edmond Lou received the B.Sc., M.Sc., and Ph.D. degrees in electrical and computer engineering from the University of Alberta, Edmonton, AB Canada, in 1991, 1993, and 1998, respectively. He is an Assistant Professor in the Department of Surgery and Adjunct Professor in Departments of Electrical and Computer Engineering, Biomedical Engineering and Pediatrics, University of Alberta. He is also a Research Scientist at the Glenrose Rehabilitation Hospital, Edmonton. His research interests include the areas of low-power instrumentation, microprocessor applications in medicine and clinical assessment of spinal deformity.


Doug Hill received the B.Sc. degree in computer engineering and the M.B.A. degree from the University of Alberta, Edmonton, AB, Canada, in 1984 and 1992, respectively. He has worked as a Clinical Engineer for most of his career. His research interests are focused on spinal deformities and translating research findings into improved outcomes for children with scoliosis. He is now a Senior Consultant with research services at the Glenrose Hospital, Edmonton, and an Adjunct assistant Professor in the Department of Surgery, University of Alberta.

Vicky H. Zhao received the B.S. and M.S. degrees from Tsinghua University, Beijing, China, in 1997 and 1999, respectively, and the Ph.D. degree from University of Maryland, College Park, in 2004. Since 2006, she has been an Assistant Professor with the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. Her research interests include media-sharing social networks, information security and forensics, digital communications, and signal processing. She is an Associate Editor for Journal of Visual Communication and Image Representation.

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Dr. Zhao is an Associate Editor for IEEE SIGNAL PROCESSING LETTERS and a Guest Editor of a special issue on signal and information processing for social learning and networking of IEEE Signal Processing Magazine.

Man-Sang Wong received the professional qualification from the School of Prosthetics and Orthotics, Hong Kong Hospital Authority, in 1988, and the M.Phil. degree in 1994 and Ph.D. degree in 2000 from The Hong Kong Polytechnic University, Hong Kong. He practiced as a Prosthetist and Orthotist in public hospitals. He pursed his research study in the orthotic management of scoliosis at The Hong Kong Polytechnic University (PolyU). He joined PolyU as an Assistant Professor in 1996 and was promoted to Associate Professor in 2004. His main research interests are scoliosis, spinal orthotics, gait and posture analysis, CAD/CAM in prosthetics and orthotics, and prosthetic and orthotic outcome evaluation.