FINAL PROJECT
Presented to
UNIVERSIDAD DE LOS ANDES
ENGINEERING FACULTY
DEPARTMENT OF BIOMEDICAL ENGINEERING
To obtain the title of
BIOMEDICAL ENGINEER
by
Daniel Kiyoshi Kuratomi Cruz
DEVELOPMENT OF A POSTURE MONITORING SYSTEM THAT
FACILITATES THE EVALUATION OF ERGONOMIC CONDITIONS
IN WORK ENVIRONMENTS
Defended May 20 of 2015 in front of:
Jury Composition
- Co-Advisor:
Mario Valderrama PhD, Assistant Professor, Universidad de Los Andes
- Co-Advisor:
Fredy Segura PhD, Associate Professor, Universidad de Los Andes
.
Contents
1 Introduction 1
1.1 Objectives . . . 1
1.1.1 General Objective . . . 1
1.1.2 Specifics Objectives . . . 1
2 Theoretical Framework 2 2.1 International Framework . . . 2
2.2 National Framework . . . 3
3 Methodology 4 3.1 Biodesign Process . . . 4
3.1.1 Identification . . . 4
3.1.2 Research . . . 4
3.1.3 Generation of Concepts . . . 4
3.1.4 Development . . . 4
4 Development 5 4.1 Identification . . . 5
4.2 Research . . . 6
4.2.1 Pathologies . . . 6
4.2.2 Posture Monitoring . . . 6
4.3 Concept Generation . . . 8
4.3.1 Brain Storming . . . 8
4.3.2 Idea Comparison . . . 9
4.4 Detailed Design . . . 10
4.4.1 Seat Module . . . 10
4.4.2 Back Plate module . . . 11
4.4.3 Sensors . . . 13
4.4.4 Control . . . 14
4.4.5 Final implementation . . . 16
5 Tests and Validation 18 5.1 Test protocols . . . 18
5.1.1 Position detection . . . 18
5.1.2 Real Environment validation . . . 18
5.2 Results . . . 19
5.2.1 Position detection . . . 19
5.2.2 Real Environment validation . . . 20
6 Discussion 22
CONTENTS iii
7 Conclusions and Future Work 24
7.1 Conclusions . . . 24 7.2 Future Work . . . 24
List of Figures
2.1 Absolute DALYs caused by Back Pain in the world, by age group. . . 3
2.2 Distribution of insured workers in Colombia . . . 3
4.1 Occupational diseases diagnosis in Colombia . . . 5
4.2 Acelerometer and position based detection of posture . . . 6
4.3 Detection of posture using Strain sensors . . . 7
4.4 Chair modification for position detection . . . 7
4.5 Cushion adaptable to different chairs . . . 8
4.6 Needs Comparison . . . 9
4.7 Idea comparison . . . 10
4.8 Position of the force sensors in the seat module . . . 11
4.9 Anatomical position of the ultrasonic sensors . . . 11
4.10 Lateral and frontal view of the structured designed . . . 12
4.11 Side-view of the structured designed . . . 12
4.12 Load cells used in the first prototype of the system . . . 13
4.13 FSR implemented in the second prototype . . . 14
4.14 Low cost ultrasonic sensors ised in the back plate . . . 14
4.15 Detailed description of the positions detected by the system . . . 15
4.16 Illustration of the positions and the principles of detection the system . . . 15
4.17 Flow chart of the decision-making of the system . . . 16
4.18 Final implementation of the control module . . . 17
4.19 Different views of the final system implemented . . . 17
5.1 Description of the experimental tests . . . 19
5.2 Height and weight distribution of the subjects . . . 19
5.3 Accuracy based on subject being studied . . . 20
5.4 Accuracy based on position detected . . . 20
5.5 Validation of the system in a real work scenario . . . 21
5.6 Accuracy based on subject in a real scenario . . . 21
6.1 Cost comparison between existing solutions in literature . . . 23
Chapter 1
Introduction
In this paper, a novel low cost two module system for monitoring seated posture is proposed with a simple haptic feedback. A biodesign process was implemented in order to address the problem of posture in occupational diseases. Several studies had created systems for the evaluation of posture using Force-Sensing Resistors, Buttons and accelerometers however none of them addressed the context of real work environments.
The system implements FSRs and Ultrasonic sensor in an adaptable and non-invasive system for massive implementation. Two sets of test protocols were proposed in order to validate the posture identification system and partial results show an 81% accuracy average.
1.1
Objectives
1.1.1
General Objective
Design and implement a system that allows the monitoring and evaluation of posture, specifically back posture, on work environments. The aim of the project is to assess and help reduce risk of formation of injuries derived from bad posture.
1.1.2
Specifics Objectives
Carry out an extensive bibliographic research about the occupational injuries that are associated with bad posture and all the technological developments that exist to monitor or treat them.
Perform an analysis of key anatomical points in order to detect bad posture.
Design a system that allows posture monitoring in working environments.
Validate the functionality of the device in a real scenario.
Chapter 2
Theoretical Framework
According to Colombian legislation, Bill 1562 of 2012, an occupational disease is contracted as a result of exposure to risk factor arising from work activity or the medium in which the worker was forced to work. There are many risk factors present in today’s modern work environments but one has become a very important without many real treatments. Even though there are many passive activities towards preventing back injuries in the workplace such as ergonomics and the training of personal, there is no real active solution to the problem of evaluating the posture of an office worker in a real work scenario.
2.1
International Framework
The National Institute for Occupational Safety and Health of the United States stated that the typical office worker spends around 50,000 hours seated in the course of his working life and as a consequence of this, around 40% of this workers develop back problems [3]. Not only at work but with the popu-larization of the Personal Computer, the amount of hours a person can be behind a desk can be even more than the estimate. Back injuries are one of the most common types of injuries in the United States and it is estimated that Americans spend over $50 Billion USD each year on treatments for this pathology.
In Europe, it is estimated that Back pain is one of the top ten pathologies that contribute to DALY’s. A DALY (Disability-adjusted life year) is a measurement of overall disease burden in terms of years lost due to illness, disability or death. Figure 2.1 shows the DALY’s caused by back problems in the world sorted by age groups. The graph shows that the most vulnerable group for this type of injury are all finishing the working period of their lives.
CHAPTER 2. THEORETICAL FRAMEWORK 3
Figure 2.1: Absolute DALYs caused by Back Pain in the world, by age group.
2.2
National Framework
In Colombia, the Federation of Colombian Insurance Companies FASECOLDA classifies workers in 5 risk categories. Class 1 workers represent low risk jobs in offices and restaurants and Class 5 workers have maximum risk jobs in the oil and mining industries. Data from this insurance companies shown in Figure 2.2 states that the biggest risk class in Colombia is Class 1 risk with 35% of all insured workers. This means that roughly 3 million workers are exposed to development of back problems and are in need of a low cost solution that will reduce the risk of acquiring this diseases.
Chapter 3
Methodology
In order to complete all the objectives of the project, a biodesign process was chosen as the work methodology. The guidelines given by it are proven to solve real biomedical problems render real solutions in academic and commercial cases. The biodesign process implemented consisted in 4 major steps, Identification and Research, Concept Generation and Implementation which are presented below.
3.1
Biodesign Process
3.1.1
Identification
The first stage consisted in the determination of the problem. This stage allowed the specification of the needs and the characterization of every stage of the problem.
3.1.2
Research
When the problem was completely defined, the bibliographic research permitted the gathering of information about it. The research stage explored the literature regarding diseases fundamentals, treatments options and the stakeholders involved in the processes detected.
3.1.3
Generation of Concepts
Using the information that was collected, and ideation stage was able generate ideas of innovative so-lutions to solve the stated problem. Using the needs characterization, the concepts were be compared and the best was selected using a quantitative method.
3.1.4
Development
In the final part, the idea that was selected was developed using a several stages of prototyping. An experimental test stage was developed in order to validate the system that was developed.
Chapter 4
Development
4.1
Identification
Analyzing data from FASECOLDA in Figure 4.1, in 2011 82% of all occupational disease diagnoses were from musculoskeletal disorders. Accounting for 40% of all diagnoses is Carpal Tunnel Syndrome (CTS), followed by Rotator Cuff Syndrome (RCS), Epicondylitis and Low Back Pain [4]. This data shows the importance of musculoskeletal disorders in occupational diseases and raised a lot of doubt to why they weren’t being treated in an active way.
Figure 4.1: Occupational diseases diagnosis in Colombia
CHAPTER 4. DEVELOPMENT 6
4.2
Research
4.2.1
Pathologies
The top 4 more prevalent musculoskeletal occupational diseases were selected as a key problem in this subject. An in depth research was done for every pathologies and important information was gathered regarding causes, treatments and current technological developments. Of the four diseases that were researched, two of them were closely related to posture, Carpal Tunnel Syndrome and Low Back Pain. This diseases have a very profound impact in public health as around 300,000 operations of CTS are carried out every year in the US and each surgery can be as high as 5,000 USD [1].
Low Back Pain is the leading cause of disability in the US for adults younger than 45 years old and is responsible for one third of worker’s compensation costs. It is estimated that the direct medical costs to treat LBP is 38 Billion USD per year. At any given time 1% of the US is chronically disabled and another 1% is temporarily disabled as a result of LBP [2].
Current treatments for this two pathologies include immobilization, therapy, medication and surgery. Prevention was only being done using training of personal and technological developments were focused on diagnostics and rehabilitation.
4.2.2
Posture Monitoring
After acquiring the new strategic focus, another iteration of research was done, this time not related to any pathology but technologies being developed to treat bad posture. Many interesting technologies were found including some commercial devices that are currently in the market.
For example, the Lumolift was launched in 2014 at a retail price of 80 USD. It integrates posture monitoring using an accelerometer in a pin that attaches to clothing and a Smartphone App that lets you track statistics about the posture of the person. Marker based position was also an expensive solution that was being analyzed by researches such as the developed by Walsh and his team [4] shown in Figure 4.16 with the commercial Lumolift.
Figure 4.2: Acelerometer and position based detection of posture
A research team from the Wearable Computing Lab of ETH University developed in 2007 a sports shirt that had embedded strain sensors as shown in Figure 4.3 in order to detect upper body posture. The system allowed a great characterization of the human movement but required that the shirt was always in contact with a major part of the subject skin which was uncomfortable in everyday use [2].
CHAPTER 4. DEVELOPMENT 7
Figure 4.3: Detection of posture using Strain sensors
Academicals research paper about the subject became very common as the problem of work related injuries became more prominent. In 2010, a Yale team developed a distribution of force sensors in a chair to assess a vibrotactile feedback in the subject. The distribution of the seven Force-Sensing resistors are shown in figure Figure 4.3 [5].
Figure 4.4: Chair modification for position detection
In 2012, a team from Shanghai University in China developed a sensing cushion using standard push-buttons in order to detect different sitting postures in the workplace. Figure 4.5 shows the distribution of the buttons and the final prototype of the cushion developed [6].
CHAPTER 4. DEVELOPMENT 8
Figure 4.5: Cushion adaptable to different chairs
4.3
Concept Generation
4.3.1
Brain Storming
After the in-depth bibliographic research was made, the information that was collected was used to devise 4 different ideas that would be able to meet the objectives in each of the 3 main categories that were detected. The 4 ideas were as followed:
Accelerometer sensors:
Use 3 accelerometers MMA7361L (3mm x 5mm x 1mm) integrated into a ”vest” as small as possible. The device would detect the gravity vector variations and that would allow the calculation of the current upper body position. The wearable device would be small but would need that the user wore it every day and charge it when the batteries were depleted.
Strain sensors:
Develop a sport shirt that can integrate the minimum amount (4) of sensors that allow the measurement of proper posture. The shirt will have the strain sensors in key positions were the most important posture positions could be identified. The limited amount of sensors would increase the comfort of the user.
Pressure sensors:
Proposal 1: Design a cushion or pad that fits most chairs and allow the measurement of position with resistive pressure sensors. The cushion would be placed in the chair and the control would be placed under the chair to reduce the total modification of the chair.
Proposal 2: Design a special chair that integrates the sensors in structure and have all the tools nec-essary to measure posture. The chair would have near perfect ergonomic conditions and would allow the best sensing interface possible.
CHAPTER 4. DEVELOPMENT 9
4.3.2
Idea Comparison
As it was not possible to develop all of them in the remaining time of the project, a need characterization was proposed in order to choose the best alternative. Taking into account the reality of Colombian society, the needs that were identified for the sensor were Resolution, Price, Comfort and Adaptability.
The resolution of the sensor is important as we wanted to have the best sensitivity in order to have a posture monitoring system that can be trusted. The price is another key factor as the median income in Colombia is not as high as the cost of some technologies, for example, a pressure distribution sensor can be as high as $3000 USD which is around a half year salary for minimum wage. Also, the final price of the solution can also limit the reach of the solution in the 3 million Class 1 workers in Colombia.
The comfort is very import as the intended user might not have any back injuries yet. According to a study of preventive methods of Low Back Pain, 58% of the people that were given Lumbar support in a group stopped using it because of Comfort [7]. The adaptability is related to the price of the solution as it allows the solution to be used by a majority rather than specific individuals that meet the requirements.
With the selected requirements, a weight comparison was carried out using the geometric mean between the four of them in relation with the Colombia context. The results of this analysis is presented in the Figure 4.6.
Figure 4.6: Needs Comparison
With the relative weight of each of the identified needs, each of the solutions that were proposed were analyzed to them. In the Figure 4.7 is the value given to each solution regarding each requirement and the weight analysis. The Total row amounts the final score each solution got. The best solution according to the context of the problem was the proposal 2 of the pressure sensors.
CHAPTER 4. DEVELOPMENT 10
Figure 4.7: Idea comparison
4.4
Detailed Design
The proposed solution aims to complement all the existent solutions and improve their performance. The main problem with the existent solutions is that their integrate force sensors in the back plate of the chair and that constrains the user to be always in contact with it if it wants to be detected by the system. In order to address this problem, a distance measuring was proposed which involve ultrasonic measurements. The system aims to maintain the accuracy of previous solutions but with a complete low-cost approach.
With this modification, the monitoring system proposed consists in two parts, the first is the cushion that is located in the seat of the chair and will integrate the force sensors and will measure the Center-Of-Pressure of the user. The second part is the structure that will hold the distance sensors that will detect the distance between the back plate of the chair and the back of the user.
4.4.1
Seat Module
For the first module of the system, the force sensors were located in order to detect small changes in position of the subject. The main pressure points of the sitting posture of a subject was analyzed and they were similar to the ones found in literature [5]. In Figure 4.8, it is shown the location of the four force sensors, located 10 cm and 25 cm down the edge of the chair.
CHAPTER 4. DEVELOPMENT 11
Figure 4.8: Position of the force sensors in the seat module
4.4.2
Back Plate module
In the design of the second module, the key points of it were the anatomical place in which the ultrasonic sensors would aim. Analyzing the anatomic measurements of a subject back, the Figure 4.9 shows that the subject has 28 cm of waist and a distance from the shoulder to the armpit of 16 cm. With this distances, a distance of 9 cm was selected as the separation of the sensors and both of them would be 8 cm lower than the shoulder line.
CHAPTER 4. DEVELOPMENT 12
With this in mind, a chair located in a Development Cubicle in was used as a model and a structure was design to position the ultrasonic sensors in the intended position. The structured that was devised accomplished two things the first is to aim the sensors precisely at the anatomical points selected and separate the back of the user of the sensor in order to have the effective range of the sensor. The structure was modeled using AutoCAD Inventor and the final results are presented in Figure 4.10 and Figure 4.11.
Figure 4.10: Lateral and frontal view of the structured designed
CHAPTER 4. DEVELOPMENT 13
4.4.3
Sensors
Analyzing the possible sensor that could be used in the implementation, the first implementation was completed using Load Cells as Figure 4.12. This type of sensor could measure up to 50 Kg and the datasheet reported very low characteristics in linearity, hysteresis and drift as well as a very low price at 9.95 USD each. The implementation of this sensors was wired with a Wheatstone bridge and the voltage difference was amplified using Instrumentation Amplifiers INA122P.
Figure 4.12: Load cells used in the first prototype of the system
Even though the initial tests of the sensors went perfect, once all four of them were implemented in the solution the measurements of all the load cells were different. The variability of two of them was higher than reported in the datasheet and didn’t withstand the load that was stated. After a few trials, 3 of the 4 sensors presented cracks in their structure which forced the change of the sensors.
The sensors that presented the next best characteristics were the Force-Sensing Resistors, or FSR, shown in Figure 4.13. This type of sensors has a high linearity reading at a very low cost, each of the sensors cost 7.95 USD. The main problem of the FSR is that it has a high hysteresis. Many papers reported hysteresis of 100 seconds that would affect the sensing value [8]. Our own sensor evaluation was done using a 0.5 Kg load on a sensor and evaluating the change. The change that was detected was 20 in 4 minutes. The effect of the hysteresis in the measurement was taken into account when designing the protocol for the final implementation.
CHAPTER 4. DEVELOPMENT 14
Figure 4.13: FSR implemented in the second prototype
The low cost ultrasonic sensors shown in Figure 4.14 have an effective range of 3cm to 500 cm. The price of this sensors is approximately 3 USD. The lower range problem was addressed with the structure that was design and the sensors where able to operate in their functional range. Even though the sensors had great accuracy detecting regular objects such as walls or notebooks, they struggled when detecting certain parts of the body and they lost some data due to the fabric of some of the shirts of the users.
Figure 4.14: Low cost ultrasonic sensors ised in the back plate
4.4.4
Control
The system was designed to detect 5 positions. The description of each of the positions is presented in Figure 4.15. They were selected based on the positions used in a similar research [5]. An illustration regarding each of the positions is presented in Figure 4.16. Also in this Figure is the graphic simulation of the changes on the sensors in the system for each of the positions that are going to be studied. As it can be observed, the Center-of-Pressure vector (Red Arrow) presents a displacement in each of the
CHAPTER 4. DEVELOPMENT 15
positions. Additionally, the distance between the back of the user and the back plate of the chair also changes between each of the positions and this will allow better accuracy of the system.
Figure 4.15: Detailed description of the positions detected by the system
Figure 4.16: Illustration of the positions and the principles of detection the system
Taking into account that the context in which the solution is needed, a fast response system is not required. In this context, a worker can spend up to 4 hours straight sitting on a chair and this allows the sensor to be able to address the hysteresis of the FSRs. The final protocol that was developed is presented in Figure 4.17. In the procedure, we let 4 minutes pass before calibrating the system.
After that, we sense the position of the user 10 times with 15 seconds separation. If after that 10 measurements the user was 70% of the time in a bad posture, the system will alert the user using the vibrotactile feedback, if not, the system will reset and wait another 4 minutes.
The aim of the project is to develop a system that will monitor sitting posture in work environments and allow people to prevent the formation of back injuries. In order to alert the user that a bad
CHAPTER 4. DEVELOPMENT 16
position is being held, a vibrotactile feedback is proposed. This haptic method would alert the user without producing any sound that would distract other workers that were close to the user and it is also the less irritating way to tell the user of the bad posture. This is very important as the system would not affect the performance of the user in the task that are being executed.
Figure 4.17: Flow chart of the decision-making of the system
4.4.5
Final implementation
After various stages of prototyping and initial testing, the final prototyped was developed using FSRs and implementing a control based on an Arduino Uno. The control presented in Figure 4.18 consists in a main control unit, an LCD screen to visualize the measurements of the sensors, a board that implements the voltage dividers for the FSRs and another board for the connection of the ultrasonic sensors and the calibration button.
CHAPTER 4. DEVELOPMENT 17
Figure 4.18: Final implementation of the control module
Figure 4.19 shows the final chair modifications that were implemented by the system. It shows the FSR implement in the seat module and the ultrasonic sensors attached to the structured that was constructed using wood.
Chapter 5
Tests and Validation
5.1
Test protocols
In order to validate the correct functionality of the system, two experimental tests were proposed. In the first one, the system accuracy for detecting each of the proposed positions will be evaluated. In the second one, a real work scenario will be used to detect the system response in this situation. A summary of both test protocols is presented in Figure 5.1.
5.1.1
Position detection
One of the test procedures that was implemented included 5 subjects and 2 randomized sets of the five positions. The subject was first trained to perform the positions using a special tool to measure the angles. After this, the calibration of the system in position 1 was done and the test began immediately. The system output is a number from 0 to 5 corresponding to each of the positions, 0 being an unidentified position. 12 Data from each position was taken every 2 seconds.
5.1.2
Real Environment validation
In order to evaluate the viability of the implementation in a working environment, the long term response of the system should be analyzed. Therefore, an experiment with 2 subjects will be performed during 1 hours with 1 recess of 5 minutes in the middle of it. In this case, the full protocol of the system will be implemented.
CHAPTER 5. TESTS AND VALIDATION 19
Figure 5.1: Description of the experimental tests
5.2
Results
5.2.1
Position detection
The system was tested with the 5 subjects as was planned. The height and weight of each of the subjects is presented in Figure 5.2 and it is important as the system has a variable response when measuring light subjects. As seen in Figure 5.3, the lightest subject had the worst accuracy levels with 65% yet the second lightest had the second highest accuracy in the trial. Figure 5.3 also shows that the average accuracy for the experimental test 1 was 79.17% which is very similar to de ones reported in the literature.
CHAPTER 5. TESTS AND VALIDATION 20
Figure 5.3: Accuracy based on subject being studied
Figure 5.4 shows the accuracy of the system based on the positions it was trying to detect. The easiest position was position 4 (Leaning backwards) as it was easily detected by the ultrasonic sensors and the force sensors. The hardest position for the system was position 2. This is due to the small differences between Center-of-Pressure vectors of positions 1 and 3.
Figure 5.4: Accuracy based on position detected
5.2.2
Real Environment validation
In order to evaluate the system in a real work scenario, 2 subjects were selected and were instructed to sit in the chair and perform regular work regarding their academic activities. The whole duration of the test was recorded using a GoPro camera that was able to record the system response in the LCD screen as seen in Figure 5.5.
CHAPTER 5. TESTS AND VALIDATION 21
Figure 5.5: Validation of the system in a real work scenario
The data of the videos was analyzed every minute and the subject position was compared to the position that the system detected. The results for each subject are sown in Figure 5.6. The results show that in a real work scenario the accuracy of the system is constant with what was found in the first trials. Even though it might appear to be a little lower, the subjects in a real work scenario were more time in position 2 which has the lower accuracy in trail 1.
Chapter 6
Discussion
The biodesign process allowed the design of a system that was able to detect several positions taking into account important variables of the work environment. The validation of the system showed a great response of the systems in the detection of the 5 positions that were being analyzed.
With the accuracy data of the system, we are able compare the proposed system with the ones found in the literature. Figure 6.1 compares 3 previous solutions to the problem of the evaluation of sitting posture. The first one by Tan and his team consisted in an expensive sensor that was put on a normal office chair. They also used a computer with MatLab to analyze the data from the sensor which made the solution very expensive.
The second solution was low-cost oriented so they used 7 Force-sensing resistors in order to detect the position. Even though the total cost of the sensors was approximately 60 USD, Zhen et al used a National Instruments DAQ as an interface to LabView to analyze the data. Again, the usage of a licensed program and a computer raise the cost of the possible solutions and limits the market.
The last project that was compared was the team of Xu that reported a very low cost of sensors. But, they also used a PC interfaced through 2 Bluetooth modules. Our solution implements very low cost sensors with a control system of only 10 USD. This allows the system to have a total cost of only 62 USD. Comparing the accuracy of the other solutions, the accuracy of the proposed system is not very far from them but it was developed with only a 10% of the total cost of the 2nd cheapest solution.
CHAPTER 6. DISCUSSION 23
Chapter 7
Conclusions and Future Work
7.1
Conclusions
Bad sitting posture is a common cause of various important occupational diseases such as Carpal Tunnel Syndrome and Low Back Pain. This diseases have a high economic impact in the health care system, only low back pain is estimated in 38 Billion USD, and a very high incidence, back pains affects 40 % of all workers.
The needs characterization allowed us to choose the best solution to the Colombian context. The modular approach of the solution that was selected increased the adaptability of the system and improved the detection of the Center-Of-Pressure with the help of the ultrasonic sensors in the back plate. The decision making of the system allowed the use of Force-Sensing Resistors without the effect of hysteresis.
The first experimental test showed an accuracy of the system (79.17%) similar to the systems that were found in the literature review. The second experimental trial validated the system in a real work environment without a significant reduction in accuracy (69.11%).
The comparison between costs of the previous solutions that were researched show the real novelty of the device. Even though the accuracy is not higher than any of the previous solutions, the cost of the proposed modular system was only a 10 % of the other solutions with improved adaptability characteristics.
7.2
Future Work
As future work, the geometry of the system should be modified in order to improve the system response for different anatomies, shorter, larger, heavier and lighter. The number of positions might be increased in order to be close to the real number of positions that the sitting posture has.
Regarding the experimental trials, more subjects should be analyzed in order to have better statistics. Also, the effect of the vibrotactile feedback in the posture of the subjects should be analyzed.
Chapter 8
References
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