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Development of a Lower Limb Exoskeleton for Improved Rehabilitation Outcomes
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Electronics.ORCID iD: 0000-0003-2878-5930
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Description
Abstract [en]

The increasing need for rehabilitation, especially among an aging population, poses challenges for healthcare systems. Exoskeletons, which integrate advanced electronics, control systems, and wireless communication, offer significant potential in rehabilitation by supporting and restoring human movement. However, realizing their full potential requires extensive research despite the technical challenges, focusing on developing intuitive interfaces, ensuring safety, and validating reliability for clinical and home use. 

This thesis sheds light on the development and validation of a model-based method to optimize exoskeleton control systems, focusing on robustness and energy efficiency. Utilizing a simulation environment, four control cases with a Linear Quadratic Regulator (LQR) are analyzed to assess performance under varying conditions and uncertainties. The impact of adjustments in the Q and R matrices within the LQR framework on system stability and power consumption is specifically examined. This approach provides insights into achieving a balanced design that is both reliable and energy-efficient, as these qualities are crucial for the future development of exoskeletons in rehabilitation. 

The thesis also explores the use of IMU sensors in smartphones as a costeffective alternative to traditional, expensive fixed motion capture systems for determining human gait cycles and joint movements, which are necessary for controlled rehabilitation. With a focus on gait recognition, the study demonstrates that these sensors can provide sufficient accuracy for various applications, suggesting their potential for rehabilitation by offering a more accessible and flexible solution. This technology could be used as a tool to recognize humans based on their joint movements, potentially improving patient recovery and expanding access to rehabilitation beyond clinical settings. 

Referring to our research results and society's need for rehabilitation devices to train patients not only in hospitals but also at home in challenging times like pandemics, we identified various design parameters, suitable motors, and materials using extensive preliminary simulations such as AnyBody modeling system to develop a functional lower leg exoskeleton. The prototype was designed to be practical and comfortable for home use. A wireless control mechanism enables remote rehabilitation exercises, allowing caregivers to monitor and adjust the process in real time, thus increasing patient autonomy and reducing clinic visits. 

Initial experiments indicated that the prototype performed as intended using a Proportional Integral Derivative (PID) controller, with high precision and fast response to remote commands while maintaining user comfort and rehabilitation effectiveness. While our prototype was constructed from aluminum alloy with the aim of home use and affordability, we recognized the importance of evaluating more sustainable materials for its construction. Therefore, we conducted a sustainability assessment using Life Cycle Assessment (LCA) methods to compare Glass Fiber Reinforced Composites (GFRC), Polycarbonate or Polylactic acid (PC/PLA) materials, and aluminum. Our findings indicate that PC/PLA materials provide a more sustainable alternative to aluminum for future exoskeleton development. Despite challenges such as sensor calibration and maintaining stable wireless communication, our study demonstrates the potential of remote-controlled lower leg exoskeletons to enhance rehabilitation accessibility and adaptability. Building on these findings, future work could focus on optimizing the technology further and conducting extensive clinical trials to assess its long-term benefits and effectiveness in rehabilitation.

Abstract [sv]

Det ökande behovet av rehabilitering, särskilt inom den åldrande befolkningen, utgör utmaningar för hälso- och sjukvårdssystemen. Exoskelett, som integrerar avancerad elektronik, styrsystem och trådlös kommunikation, erbjuder betydande potential inom rehabilitering genom att stödja och återställa mänsklig rörelse. För att realisera deras fulla potential krävs dock omfattande forskning för att övervinna tekniska utmaningar, med fokus på att utveckla intuitiva gränssnitt, säkerställa säkerhet och validera tillförlitlighet för såväl kliniskt bruk som för hemmabruk. 

Denna avhandling belyser utvecklingen och valideringen av en modellbaserad metod för att optimera exoskelettets styrsystem, med fokus på robusthet och energieffektivitet. Genom att utnyttja en simuleringsmiljö analyseras fyra styrfall med en linjär-kvadratisk regulator (LQR) för att bedöma prestanda under varierande förhållanden och osäkerheter. Särskild uppmärksamhet ägnas åt effekten av justeringar i Q- och R-matriserna inom LQR-ramverket på systemets stabilitet och energiförbrukning. Denna metod ger förståelse för i hur man uppnår en balanserad design som är både pålitlig och energieffektiv, vilket kan vara avgörande för framtida utveckling av exoskelett inom rehabilitering. 

Avhandlingen utforskar också användningen av IMU sensorer i smartphones som ett kostnadseffektivt alternativ till traditionella dyra, fasta rörelsedetektionssystem för att bestämma mänskliga gångcykler och ledrörelser, vilket är nödvändigt för kontrollerad rehabilitering. Med focus på gångigenkänning visar studien att dessa sensorer kan ge tillräcklig noggrannhet för olika applikationer, vilket antyder deras potential för rehabilitering genom att erbjuda en mer tillgänglig och flexibel lösning. Denna teknologi kan användas som ett effektivt verktyg för att känna igen människor baserat på deras ledrörelser, vilket kan avsevärt förbättra patienternas återhämtning och utöka tillgången till rehabilitering bortom kliniska miljöer. 

Vårt arbete i kombination med samhällets behov av rehabilitering för att träna patienter, inte bara på sjukhus utan också hemma, identifierade olika designparametrar såsom, till exempel vridmoment. Detta styrde valet av lämpliga motorer. Omfattande preliminära simuleringar med AnyBody-modelleringssystemet för att utveckla ett funktionellt exoskelett för underbenet har utförts. En prototyp utformades för att vara praktisk och bekväm för hemmabruk. En trådlös styrmekanism möjliggör fjärrstyrda rehabiliteringsövningar, vilket tillåter vårdgivare att övervaka och justera processen i realtid, därmed öka patientens autonomi och minska klinikbesök. 

Inledande experiment visade att prototypen presterade som avsett med användning av en PID-regulator, med hög precision och snabb respons på fjärrstyrningskommandon, samtidigt som användarkomfort och rehabiliteringseffektivitet bibehölls. För att kunna överföra prototypen till en produkt lämplig för hemmabruk krävs ett lättare men starkare material än den aluminiumlegering vi använt. Därför genomförde vi en hållbarhetsbedömning med hjälp av livscykelanalys (LCA) för att jämföra glasfiberarmerade kompositer (GFRC), Polykarbonat eller Polylaktid (PC/PLA) material och aluminium. Analysen visar att PC/PLA-material erbjuder ett mer hållbart alternativ än aluminium för framtida exoskelettutveckling. Trots utmaningar som sensorkalibrering och att upprätthålla stabil trådlös kommunikation, visar vår studie att fjärrstyrda exoskelett för underbenet har potential att förbättra tillgänglighet och anpassningsbarhet inom rehabilitering. Utifrån dessa resultat skulle framtida arbete kunna fokusera på att ytterligare optimera teknologin och genomföra omfattande kliniska studier för att utvärdera dess långsiktiga fördelar och effektivitet inom rehabilitering.

Place, publisher, year, edition, pages
Gävle: Gävle University Press , 2024. , p. 42
Series
Doctoral thesis ; 51
Keywords [en]
Rehabilitation Exoskeleton, Robust Controller, Energy Consumption, LQR Control, Inertial Measurement Unit (IMU), PID Controller, WEKA, Machine Learning Classification
Keywords [sv]
Exoskelett för rehabiliterings, robust reglering, energiförbrukning, LQR reglering, Inertial Measurement Unit (IMU), PID-regulator, WEKA, maskininlärningsklassificering
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-45777ISBN: 978-91-89593-44-2 (print)ISBN: 978-91-89593-45-9 (electronic)OAI: oai:DiVA.org:hig-45777DiVA, id: diva2:1903440
Public defence
2025-01-23, 12:108, Kungsbäcksvägen 47, Gävle, 13:00 (English)
Opponent
Supervisors
Available from: 2024-12-18 Created: 2024-10-04 Last updated: 2024-12-18
List of papers
1. The MATLAB Simulation and the Linear Quadratic Regulator Torque Control of a Series Elastic Actuator for a Rehabilitation Hip Exoskeleton
Open this publication in new window or tab >>The MATLAB Simulation and the Linear Quadratic Regulator Torque Control of a Series Elastic Actuator for a Rehabilitation Hip Exoskeleton
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Almost the half of mechanical energy of a human gait cycle is generated by a hip joint. Therefore, this paper discusses a rehabilitation hip exoskeleton, starting with the modeling, simulation and ending with controlling its hip joints. A MATLAB based simulation environment with the use of Simscape Multibody toolbox was utilized to design and control the robotic hip exoskeleton. More details of adding a series elastic actuators (SEA) to the hip joints with the mathematical model are presented. However, the linearised mathematical model of the entire exoskeleton was found in simulation software which establish the basic need of controlling hip joints. The trajectory tracking is commonly used of controlling rehabilitation exoskeleton and to ensure a safe and reliable motion tracking methods, two desired torque signals were tested and analysed with the optimal linear quadratic regulator (LQR). The experiments with two torque signals–representing the sit-to-stand (STS) and the walking activity, demonstrated good performance of the motion gait tracking based on torque signals of a healthy person, which is carried out in the simulation environment. Furthermore, some studies in a human robot interaction are also mentioned in this paper.

Place, publisher, year, edition, pages
IEEE, 2022
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-40339 (URN)10.1109/IRCE55557.2022.9963074 (DOI)2-s2.0-85141841415 (Scopus ID)978-1-6654-6995-1 (ISBN)
Conference
IRCE 2022: The 5th International Conference on Intelligent Robotics and Control Engineering, Tianjin, China, September 23-25, 2022
Available from: 2022-11-01 Created: 2022-11-01 Last updated: 2024-10-30Bibliographically approved
2. The Energy Consumption and Robust Case Torque Control of a Rehabilitation Hip Exoskeleton
Open this publication in new window or tab >>The Energy Consumption and Robust Case Torque Control of a Rehabilitation Hip Exoskeleton
2022 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 12, no 21, article id 11104Article in journal (Refereed) Published
Abstract [en]

Gait disorders, muscle weakness, spinal cord injuries (SCIs) and other work-related disorders have increased the need for rehabilitation exoskeletons—specifically, for the hip because a huge percentage of mechanical power comes from the hip joint. However, realising a lightweight rehabilitation hip exoskeleton for mobility and at-home use with reliable control is challenging. The devices developed are restricted by a joint actuator and energy source design and tend to have various uncertainties. Thus, this study tested the robustness of four optimal controller cases in a simulation-based environment. We sought to determine whether the most robust optimal controller consumed less energy and demonstrated better performance in tracking the desired signal. The robustness of the optimal cases was tested with the hip torque signals of healthy subjects. The number of sit-to-stand (STS) instances and the walking distance at various speeds were calculated. The results showed that the most robust case controller was more energy efficient for STS, but not for walking activity. Furthermore, this study provides compelling evidence that various optimal controllers have different degrees of robustness and effects on energy consumption.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
exoskeleton; robust controller; energy consumption; hip rehabilitation exoskeleton; series elastic actuator (SEA); LQR control; Luenberger state observer; torque control
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-40337 (URN)10.3390/app122111104 (DOI)000880886800001 ()2-s2.0-85141885003 (Scopus ID)
Available from: 2022-11-01 Created: 2022-11-01 Last updated: 2024-10-04Bibliographically approved
3. Smartphone IMU Sensors for Human Identification through Hip Joint Angle Analysis
Open this publication in new window or tab >>Smartphone IMU Sensors for Human Identification through Hip Joint Angle Analysis
Show others...
2024 (English)In: Sensors, E-ISSN 1424-8220, Vol. 24, no 15, article id 4769Article in journal (Refereed) Published
Abstract [en]

Gait monitoring using hip joint angles offers a promising approach for person identification, leveraging the capabilities of smartphone inertial measurement units (IMUs). This study investigates the use of smartphone IMUs to extract hip joint angles for distinguishing individuals based on their gait patterns. The data were collected from 10 healthy subjects (8 males, 2 females) walking on a treadmill at 4 km/h for 10 min. A sensor fusion technique that combined accelerometer, gyroscope, and magnetometer data was used to derive meaningful hip joint angles. We employed various machine learning algorithms within the WEKA environment to classify subjects based on their hip joint pattern and achieved a classification accuracy of 88.9%. Our findings demonstrate the feasibility of using hip joint angles for person identification, providing a baseline for future research in gait analysis for biometric applications. This work underscores the potential of smartphone-based gait analysis in personal identification systems.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
smartphone sensors; IMU sensors; person recognition; machine learning classification; human motion analysis
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-45273 (URN)10.3390/s24154769 (DOI)001287010600001 ()39123816 (PubMedID)2-s2.0-85200860251 (Scopus ID)
Projects
PID2022-1375250B-C21
Available from: 2024-07-25 Created: 2024-07-25 Last updated: 2024-10-04Bibliographically approved
4. The Information Fusion on Person Recognition Using Hip Joint Angles
Open this publication in new window or tab >>The Information Fusion on Person Recognition Using Hip Joint Angles
2024 (English)In: 2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), IEEE , 2024, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

In this research, we investigate the efficacy of information fusion techniques for the purpose of gait pattern recognition using hip joint angle data captured by smartphone sensors. The classifiers tested were the Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naive Bayes (NB) algorithms, which gave the highest classification accuracy. But, to further enhance the classification accuracy, we integrated score-level fusion (SLF) and decision-level fusion (DLF), leveraging multiple classifier algorithms. Our experiment results reveal that information fusion techniques improve the overall accuracy with 90.5% for the score-level fusion and 91% for the decision-level fusion (voting scheme), indicating the effectiveness of ensemble methods in hip joint angle-based recognition systems. Lastly, some Limitations of the study, such as the use of treadmills and the focus on healthy adult gait patterns are recognized, highlighting areas for future research, including the application to individuals with gait-affecting conditions.

Place, publisher, year, edition, pages
IEEE, 2024
Keywords
decision level fusion; information fusion; KNN; machine learning classification; NB; score level fusion; SVM
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-45636 (URN)10.1109/iciea61579.2024.10664846 (DOI)001323563900107 ()2-s2.0-85205720348 (Scopus ID)979-8-3503-6086-8 (ISBN)
Conference
2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), Kristiansand, Norway, 5-8 August 2024
Available from: 2024-09-19 Created: 2024-09-19 Last updated: 2025-01-20Bibliographically approved
5. Exploring the Influence of a Passive Exoskeleton on Range of Motion and Step Length During Walking
Open this publication in new window or tab >>Exploring the Influence of a Passive Exoskeleton on Range of Motion and Step Length During Walking
2024 (English)In: 2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), IEEE , 2024, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, commercial exoskeletons have seen widespread use across various industrial processes, offering assistance in tasks that are physically demanding for humans. While exoskeletons enhance task performance, it's crucial to understand their impact during periods of non-task activities, such as walking between workstations. This study utilized IMU sensors to investigate potential differences in gait dynamics when individuals walk with and without exoskeleton assistance. Our research reveals notable discrepancies in both range of motion (ROM) and step length when individuals employ exoskeletons during non-task-related walking. These disparities were investigated through the extraction of gait joint angles' features and the application of classification algorithms.

Place, publisher, year, edition, pages
IEEE, 2024
Keywords
Gait pattern, IMU sensors, exoskeleton, range of motion, step length, features, machine learning classification.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-45635 (URN)10.1109/iciea61579.2024.10665200 (DOI)001323563900303 ()2-s2.0-85205700552 (Scopus ID)979-8-3503-6086-8 (ISBN)
Conference
2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), Kristiansand, Norway, 5-8 August 2024
Available from: 2024-09-19 Created: 2024-09-19 Last updated: 2024-12-04Bibliographically approved
6. Wireless PID-Based Control for a Single-Legged Rehabilitation Exoskeleton
Open this publication in new window or tab >>Wireless PID-Based Control for a Single-Legged Rehabilitation Exoskeleton
2024 (English)In: Machines, E-ISSN 2075-1702, Vol. 12, no 11, article id 745Article in journal (Refereed) Published
Abstract [en]

The demand for remote rehabilitation is increasing, opening up convenient and effective home-based therapy for the sick and elderly. In this study, we use AnyBody simulations to analyze muscle activity and determine key parameters for designing a rehabilitation exoskeleton, as well as selecting the appropriate motor torque to assist patients during rehabilitation sessions. The exoskeleton was designed with a PID control mechanism for the precise management of motor positions and joint torques, and it operates in both automated and teleoperation modes. Hip and knee movements are monitored via smartphone-based IMU sensors, enabling real-time feedback. Bluetooth communication ensures seamless control during various training scenarios. Our study demonstrates that remotely controlled rehabilitation systems can be implemented effectively, offering vital support not only during global health crises such as pandemics but also in improving the accessibility of rehabilitation services in remote or underserved areas. This approach has the potential to transform the way physical therapy can be delivered, making it more accessible and adaptable to the needs of a larger patient population.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
rehabilitation exoskeleton; PID control; AnyBody simulation; IMU sensors; hip joint trajectory; Bluetooth communication
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Control Engineering Robotics Telecommunications Mechanical Engineering Public Health, Global Health, Social Medicine and Epidemiology Biomedical Laboratory Science/Technology Physiotherapy
Identifiers
urn:nbn:se:hig:diva-45872 (URN)10.3390/machines12110745 (DOI)001365600700001 ()2-s2.0-85210168484 (Scopus ID)
Available from: 2024-10-22 Created: 2024-10-22 Last updated: 2024-12-12Bibliographically approved
7. The Sustainable Assessment for a Rehabilitation Lower Limb Exoskeleton
Open this publication in new window or tab >>The Sustainable Assessment for a Rehabilitation Lower Limb Exoskeleton
2024 (English)In: 2024 International Conference on Decision Aid Sciences and Applications (DASA), Bahrain: IEEE, 2024Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Bahrain: IEEE, 2024
Keywords
Lower limb exoskeleton, Life Cycle Assessment (LCA), environmental impact, rehabilitation at home, GFRC, PC/PLA materials. I. INTRODUCTION
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Robotics Environmental Biotechnology Other Environmental Biotechnology
Identifiers
urn:nbn:se:hig:diva-46031 (URN)
Conference
2024 International Conference on Decision Aid Sciences and Applications (DASA), 11-12 December, Bahrain
Note

kommande

Available from: 2024-11-17 Created: 2024-11-17 Last updated: 2024-11-19Bibliographically approved

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