| 1. |
- Bentes, João, 1988-, et al.
(författare)
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Novel System Architecture for Online Gait Analysis
- 2017
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Konferensbidrag (refereegranskat)abstract
- Although wearable devices can be used to perform continuous gait analysis in daily life, existing platforms only support short-term analysis in quasi-controlled environments. This paper proposes a novel system architecture that is designed for long-term, online gait analysis in free-living environments. Various aspects related to the feasibility and scalability of the proposed system are presented.
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| 2. |
- Byttner, Stefan, 1975-, et al.
(författare)
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An ion current algorithm for fast determination of high combustion variability
- 2004
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Ingår i: SAE Technical Paper Series. - 400 Commonwealth Drive, Warrendale, PA, United States : SAE International. - 0148-7191.
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Konferensbidrag (refereegranskat)abstract
- It is desirable for an engine control system to maintain a stable combustion. A high combustion variability (typically measured by the relative variations in produced work, COV(IMEP)) can indicate the use of too much EGR or a too lean air-fuel mixture, which results in less engine efficiency(in terms of fuel and emissions) and reduced driveability. The coefficient of variation (COV) of the ion current integral has previously been shown in several papers to be correlated to the coefficient of variation of IMEP for various disturbances (e.g. AFR, EGR and fuel timing). This paper presents a cycle-to-cycle ion current based method of estimating the approximate category of IMEP (either normal burn, slow burn, partial burn or misfire) for the case of lean air-fuel ratio. The rate of appearance of the partial burn and misfire categories is then shown to be well correlated with the onset of high combustion variability(high COV(IMEP)). It is demonstrated that the detection of these categories can result in faster determination(prediction) of high variability compared to only using the COV(Ion integral). Copyright © 2004 SAE International.
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| 3. |
- Byttner, Stefan, 1975-, et al.
(författare)
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Estimation of combustion variability using in-cylinder ionization measurements
- 2001
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Konferensbidrag (refereegranskat)abstract
- This paper investigates the use of the ionization current to estimate the Coefficient of Variation for the Indicated Mean Effective Pressure, COV(IMEP), which is a common variable for combustion stability in a spark-ignited engine. Stable combustion in this definition implies that the variance of the produced work, measured over a number of consecutive combustion cycles, is small compared to the mean of the produced work. The COV(IMEP) is varied experimentally either by increasing EGR flow or by changing the air-fuel ratio, in both a laboratory setting (engine in dynamometer) and in an on-road setting. The experiments show a positive correlation between COV(Ion integral), the Coefficient of Variation for the integrated Ion Current, and COV(IMEP), when measured under low load on an engine in a dynamometer, but not under high load conditions. On-road experiments show a positive correlation, but only in the EGR and the lean burn case. An approach based on individual cycle classification for real-time estimation of combustion stability is discussed. © Copyright 2001 Society of Automotive Engineers, Inc.
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| 4. |
- Byttner, Stefan, 1975-, et al.
(författare)
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Strategies for handling the fuel additive problem in neural network based ion current interpretation
- 2001
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Ingår i: SAE Technical Paper Series. - Warrendale, PA : Society of Automotive Engineers. - 0148-7191.
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Konferensbidrag (refereegranskat)abstract
- With the introduction of unleaded gasoline, special fuel agents have appeared on the market for lubricating and cleaning the valve seats. These fuel agents often contain alkali metals that have a significant impact on the ion current signal, thus affecting strategies that use the ion current for engine control and diagnosis, e.g., for estimating the location of the pressure peak. This paper introduces a method for making neural network algorithms robust to expected disturbances in the input signal and demonstrates how well this method applies to the case of disturbances to the ion current signal due to fuel additives containing sodium. The performance of the neural estimators is compared to a Gaussian fit algorithm, which they outperform. It is also shown that using a fuel additive significantly improves the estimation of the location of the pressure peak. © 2001 Society of Automotive Engineers, Inc.
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| 5. |
- Jonsson, Magnus, 1969-, et al.
(författare)
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Vision-based low-level navigation using a feed-forward neural network
- 1997
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Ingår i: Proc. International Workshop on Mechatronical Computer Systems for Perception and Action (MCPA'97), Pisa, Italy, Feb. 10-12. ; , s. 105-111
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose a simple method for low-level navigation for autonomous mobile robots, employing an artificial neural network. Both corridor following and obstacle avoidance in indoor environments are managed by the same network. Raw grayscale images of size 32 x 23 pixels are processed one at a time by a feed-forward neural network. The output signals from the network directly control the motor control system of the robot. The feed-forward network is trained using the RPROP algorithm. Experiments in both familiar and unfamiliar environments are reported.
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| 6. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Detecting Gait Events from Outdoor Accelerometer Data for Long-term and Continuous Monitoring Applications
- 2014
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Ingår i: 13th International Symposium on 3D Analysis of Human Movement. - 9782880748562 ; , s. 151-154
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Konferensbidrag (refereegranskat)abstract
- Detecting gait events is the key to many gait analysis applications which would immensely benefit if the analysis could be carried out using wearable sensors in uncontrolled outdoor environments, enabling continuous monitoring and long-term analysis. This would allow exploring new frontiers in gait analysis by facilitating the availability of more data and empower individuals, especially patients, to avail the benefits of gait analysis in their everyday lives. Previous gait event detection algorithms impose many restrictions as they have been developed from data collected incontrolled, indoor environments. This paper proposes a robust algorithm that utilizes a priori knowledge of gait in conjunction with continuous wavelet transform analysis, to accurately identify heel strike and toe off, from noisy accelerometer signals collected during indoor and outdoor walking. The accuracy of the algorithm is evaluated by using footswitches that are considered as ground truth and the results are compared with another recently published algorithm.
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| 7. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database
- 2017
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Ingår i: Gait & Posture. - Amsterdam : Elsevier. - 0966-6362 .- 1879-2219. ; 51, s. 84-90
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Tidskriftsartikel (refereegranskat)abstract
- Numerous gait event detection (GED) algorithms have been developed using accelerometers as they allow the possibility of long-term gait analysis in everyday life. However, almost all such existing algorithms have been developed and assessed using data collected in controlled indoor experiments with pre-defined paths and walking speeds. On the contrary, human gait is quite dynamic in the real-world, often involving varying gait speeds, changing surfaces and varying surface inclinations. Though portable wearable systems can be used to conduct experiments directly in the real-world, there is a lack of publicly available gait datasets or studies evaluating the performance of existing GED algorithms in various real-world settings.This paper presents a new gait database called MAREA (n=20 healthy subjects) that consists of walking and running in indoor and outdoor environments with accelerometers positioned on waist, wrist and both ankles. The study also evaluates the performance of six state-of-the-art accelerometer-based GED algorithms in different real-world scenarios, using the MAREA gait database. The results reveal that the performance of these algorithms is inconsistent and varies with changing environments and gait speeds. All algorithms demonstrated good performance for the scenario of steady walking in a controlled indoor environment with a combined median F1score of 0.98 for Heel-Strikes and 0.94 for Toe-Offs. However, they exhibited significantly decreased performance when evaluated in other lesser controlled scenarios such as walking and running in an outdoor street, with a combined median F1score of 0.82 for Heel-Strikes and 0.53 for Toe-Offs. Moreover, all GED algorithms displayed better performance for detecting Heel-Strikes as compared to Toe-Offs, when evaluated in different scenarios. © 2016 Elsevier B.V.
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| 8. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Gait Event Detection in Real-World Environment for Long-Term Applications : Incorporating Domain Knowledge into Time-Frequency Analysis
- 2016
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Ingår i: IEEE transactions on neural systems and rehabilitation engineering. - Piscataway, NJ : IEEE Press. - 1534-4320 .- 1558-0210. ; 24:12, s. 1363-1372
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Tidskriftsartikel (refereegranskat)abstract
- Detecting gait events is the key to many gait analysis applications that would benefit from continuous monitoring or long-term analysis. Most gait event detection algorithms using wearable sensors that offer a potential for use in daily living have been developed from data collected in controlled indoor experiments. However, for real-word applications, it is essential that the analysis is carried out in humans’ natural environment; that involves different gait speeds, changing walking terrains, varying surface inclinations and regular turns among other factors. Existing domain knowledge in the form of principles or underlying fundamental gait relationships can be utilized to drive and support the data analysis in order to develop robust algorithms that can tackle real-world challenges in gait analysis. This paper presents a novel approach that exhibits how domain knowledge about human gait can be incorporated into time-frequency analysis to detect gait events from longterm accelerometer signals. The accuracy and robustness of the proposed algorithm are validated by experiments done in indoor and outdoor environments with approximately 93,600 gait events in total. The proposed algorithm exhibits consistently high performance scores across all datasets in both, indoor and outdoor environments. © Copyright 2016 IEEE
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| 9. |
- Khandelwal, Siddhartha, 1987-
(författare)
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Gait Event Detection in the Real World
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Healthy gait requires a balance between various neuro-physiological systems and is considered an important indicator of a subject's physical and cognitive health status. As such, health-related applications would immensely benefit by performing long-term or continuous monitoring of subjects' gait in their natural environment and everyday lives. In contrast to stationary sensors such as motion capture systems and force plates, inertial sensors provide a good alternative for such gait analysis applications as they are miniature, cheap, mobile and can be easily integrated into wearable systems.This thesis focuses on improving overall gait analysis using inertial sensors by providing a methodology for detecting gait events in real-world settings. Although the experimental protocols for such analysis have been restricted to only highly-controlled lab-like indoor settings; this thesis presents a new gait database that consists of data from gait activities carried out in both, indoor and outdoor environments. The thesis shows how domain knowledge about gait could be formulated and utilized to develop methods that are robust and can tackle real-world challenges. It also shows how the proposed approach can be generalized to estimate gait events from multiple body locations. Another aspect of this thesis is to demonstrate that the traditionally used temporal error metrics are not enough for presenting the overall performance of gait event detection methods. The thesis introduces how non-parametric tests can be used to complement them and provide a better overview.The results of comparing the proposed methodology to state-of-the-art methods showed that the approach of incorporating domain knowledge into the time-frequency analysis of the signal was robust across different real-world scenarios and outperformed other methods, especially for the scenario involving variable gait speeds in outdoor settings. The methodology was also benchmarked on publicly available gait databases yielding good performance for estimating events from different body locations. To conclude, this thesis presents a road map for the development of gait analysis systems in real-world settings.
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| 10. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Identification of Gait Events using Expert Knowledge and Continuous Wavelet Transform Analysis
- 2014
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Ingår i: BIOSIGNALS 2014. - [S.l.] : SciTePress. - 9789897580116 ; , s. 197-204
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Konferensbidrag (refereegranskat)abstract
- Many gait analysis applications involve long-term or continuous monitoring which require gait measurements to be taken outdoors. Wearable inertial sensors like accelerometers have become popular for such applications as they are miniature, low-powered and inexpensive but with the drawback that they are prone to noise and require robust algorithms for precise identification of gait events. However, most gait event detection algorithms have been developed by simulating physical world environments inside controlled laboratories. In this paper, we propose a novel algorithm that robustly and efficiently identifies gait events from accelerometer signals collected during both, indoor and outdoor walking of healthy subjects. The proposed method makes adept use of prior knowledge of walking gait characteristics, referred to as expert knowledge, in conjunction with continuous wavelet transform analysis to detect gait events of heel strike and toe off. It was observed that in comparison to indoor, the outdoor walking acceleration signals were of poorer quality and highly corrupted with noise. The proposed algorithm presents an automated way to effectively analyze such noisy signals in order to identify gait events.
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| 11. |
- Khandelwal, Siddhartha, 1987-, et al.
(författare)
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Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations
- 2018
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Ingår i: Gait & Posture. - Amsterdam : Elsevier. - 0966-6362 .- 1879-2219. ; 59, s. 278-285
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Tidskriftsartikel (refereegranskat)abstract
- Identifying Initial Contact events (ICE) is essential in gait analysis as they segment the walking pattern into gait cycles and facilitate the computation of other gait parameters. As such, numerous algorithms have been developed to identify ICE by placing the accelerometer at a specific body location. Simultaneously, many researchers have studied the effects of device positioning for participant or patient compliance, which is an important factor to consider especially for long-term studies in real-life settings. With the adoption of accelerometery for long-term gait analysis in daily living, current and future applications will require robust algorithms that can either autonomously adapt to changes in sensor positioning or can detect ICE from multiple sensors locations.This study presents a novel methodology that is capable of estimating ICE from accelerometers placed at different body locations. The proposed methodology, called DK-TiFA, is based on utilizing domain knowledge about the fundamental spectral relationships present between the movement of different body parts during gait to drive the time-frequency analysis of the acceleration signal. In order to assess the performance, DK-TiFA is benchmarked on four large publicly available gait databases, consisting of a total of 613 subjects and 7 unique body locations, namely, ankle, thigh, center waist, side waist, chest, upper arm and wrist. The DK-TiFA methodology is demonstrated to achieve high accuracy and robustness for estimating ICE from data consisting of different accelerometer specifications, varying gait speeds and different environments. © 2017 Elsevier B.V.
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| 12. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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A Database-Centric Architecture for Home-Based Health Monitoring
- 2013
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Ingår i: Ambient Assisted Living and Active Aging. - Heidelberg, Germany : Springer. - 9783319030913 - 9783319030920 ; , s. 26-34
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Bokkapitel (refereegranskat)abstract
- Traditionally, database management systems (DBMSs) have been employed exclusively for data management in infrastructures supporting Ambient Assisted Living (AAL) systems. However, DBMSs provide other mechanisms, such as for security, dependability, and extensibility that can facilitate the development, use, and maintenance of AAL applications. This work utilizes such mechanisms, particularly extensibility, and proposes a database-centric architecture to support home-based healthcare applications. An active database is used to monitor and respond to events taking place in the home, such as bed-exits. In-database data mining methods are applied to model early night behaviors of people living alone. Encapsulating the processing into the DBMS avoids transferring and processing sensitive data outside of database, enables changes in the logic to be managed on-the-fly, and reduces code duplication. As a result, such an approach leads to better performance and increased security and privacy, and can facilitate the adaptability and scalability of AAL systems. An evaluation of the architecture with datasets collected in real homes demonstrated the feasibility and flexibility of the approach.
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| 13. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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A lightweight method for detecting sleep-related activities based on load sensing
- 2014
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Ingår i: SeGAH 2014. - Red Hook, NY : Curran Associates, Inc.. - 9781479948239
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Konferensbidrag (refereegranskat)abstract
- Current practices in healthcare rely on expensive and labor-intensive procedures that are not adequate for future healthcare demands. Therefore, alternatives are required to complement or enhance healthcare services, both at clinical and home settings. Hospital and ordinary beds can be equipped with load cells to enable load sensing applications, such as for weight and sleep assessment. Beds with such functionalities represent a tangible alternative to expensive and obtrusive routines for sleep assessment, such as polysomnography. A finite-state machine is proposed as a lightweight on-line method to detect sleep-related activities, such as bed entrances and exits, awakenings, wakefulness, and sleep atonia. The proposed approach is evaluated with a dataset collected in real homes of older people receiving night-time home care services.
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| 14. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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A "Smart Bedroom" as an Active Database System
- 2013
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Ingår i: Proceedings – 9th International Conference on Intelligent Environments, IE 2013. - Los Alamitos, CA : IEEE Computer Society. - 9780769550381 - 9781479907458 ; , s. 250-253
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Konferensbidrag (refereegranskat)abstract
- Home-based healthcare technologies aim to enable older people to age in place as well as to support those delivering care. Although a number of smart homes exist, there is no established method to architect these systems. This work proposes the development of a smart environment as an active database system. Active rules in the database, in conjunction with sensors and actuators, monitor and respond to events taking place in the home environment. Resource adapters integrate heterogeneous hardware and software technologies into the system. A 'Smart Bedroom' has been developed as a demonstrator. The proposed approach represents a flexible and robust architecture for smart homes and ambient assisted living systems. © 2013 IEEE.
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| 15. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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Active In-Database Processing to Support Ambient Assisted Living Systems
- 2014
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Ingår i: Sensors. - Basel : Multidisciplinary Digital Publishing Institute AG. - 1424-8220. ; 14:8, s. 14765-14785
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Tidskriftsartikel (refereegranskat)abstract
- As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.
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| 16. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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Ambient Intelligence and Robotics : complementing one another to support Ambient Assisted Living
- 2014
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Ingår i: IAS-13. - 9788895872063
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Konferensbidrag (refereegranskat)abstract
- This work combines a database-centric architecture, which supports Ambient Intelligence (AmI) for Ambient Assisted Living, with a ROS-based mobile sensing and interaction robot. The role of the active database is to monitor and respond to events in the environment and the robot subscribes to tasks issued by the AmI system. The robot can autonomously perform tasks such as to search for and interact with a person. Consequently, the two systems combine their capabilities and complement the lack of computational, sensing and actuation resources.
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| 17. |
- Ourique de Morais, Wagner, 1979-, et al.
(författare)
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Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments
- 2015
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Rapport (refereegranskat)abstract
- Advances in database technology allow modern database systems to serve as a platform for the development, deployment and management of smart home environments and ambient assisted living systems. This work investigates non-functional issues of a database-centric system architecture for smart home environments when: (i) extending the system with new functionalities other than data storage, such as on-line reactive behaviors and advanced processing of longitudinal information, (ii) porting the whole system to different operating systems on distinct hardware platforms, and (iii) scaling the system by incrementally adding new instances of a given functionality. The outcome of the evaluation is demonstrated, and analyzed, for three test functionalities on three heterogeneous computing platforms. As a contribution, this work can help developers in identifying which architectural components in the database-centric system architecture that may become performance bottlenecks when extending, porting and scaling the system.
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| 18. |
- Sant'Anna, Anita, 1983-, et al.
(författare)
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A wearable gait analysis system using inertial sensors Part I : Evaluation of measures of gait symmetry and normality against 3D kinematic data
- 2012
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Ingår i: BIOSIGNALS 2012 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing. - [S. l.] : SciTePress. - 9789898425898 ; , s. 180-188
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Konferensbidrag (refereegranskat)abstract
- Gait analysis (GA) is an important tool in the assessment of several physical and cognitive conditions. The lack of simple and economically viable quantitative GA systems has hindered the routine clinical use of GA in many areas. As a result, patients may be receiving sub-optimal treatment. The present study introduces and evaluates measures of gait symmetry and gait normality calculated from inertial sensor data. These indices support the creation of mobile, cheap and easy to use quantitative GA systems. The proposed method was compared to measures of symmetry and normality derived from 3D kinematic data. Results show that the proposed method is well correlated to the kinematic analysis in both symmetry (r=0.84, p<0.0001) and normality (r=0.81, p<0.0001). In addition, the proposed indices can be used to classify normal from abnormal gait.
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| 19. |
- Sant'Anna, Anita, 1983-, et al.
(författare)
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A wearable gait analysis system using inertial sensors Part II: Evaluation in clinical setting.
- 2012
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Ingår i: Proceedings of the International Conference on Bio-inspired systems and signal processing, BIOSIGNALS 2012. - [S. l.] : SciTePress. - 9789898425898 ; , s. 5-14
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Konferensbidrag (refereegranskat)abstract
- The gold standard for gait analysis, in-lab 3D motion capture, is not routinely used for clinical assessment due to limitations in availability, cost and required training. Inexpensive alternatives to quantitative gait analysis are needed to increase the its adoption. Inertial sensors such as accelerometers and gyroscopes are promising tools for the development of wearable gait analysis (WGA) systems. The present study evaluates the use of a WGA system on hip-arthroplasty patients in a real clinical setting. The system provides information about gait symmetry and normality. Results show that the normality measurements are well correlated with various quantitative and qualitative measures of recovery and health status.
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| 20. |
- Sant'Anna, Anita, 1983-, et al.
(författare)
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Developing a Motion Language: Gait Analysis from Accelerometer Sensor Systems
- 2009
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Ingår i: Pervasive Health 2009. - Piscataway, N.J. : IEEE Press. - 9789639799424 ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- The advances in sensing technology provide us with the opportunity to develop mobile and unobtrusive systems to continuously gather gait data. Accelerometers have been shown to be an adequate choice for recording human motion data. For that reason, many previous works have investigated the use of accelerometers for gait analysis. Previous works were able to extract either static temporal information or dynamic general information about the gait patterns. This work aims at extracting both static and dynamic information from acceleration signals. The ability to extract information about the dynamics of gait is exemplified with a novel symmetry measure. The method presented here is based on the motion language approach. A method based on peak detection was chosen as a reference, which we compare to our method. A Gait Rite pressure sensitive mat was used to detect heel-strike and toe-off ground truths. Results show that the proposed approach is as accurate as, more robust than, and conveys more information than the reference method.
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| 21. |
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| 22. |
- Weman-Josefsson, Karin Anna, 1975-, et al.
(författare)
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Digital Innovations and Self-determined exercise motivation : an interdisciplinary approach
- 2015
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Ingår i: Proceedings of The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC March 2015. Orlando, Florida..
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Konferensbidrag (refereegranskat)abstract
- In face of escalating health care costs, new technology holds great promise for innovative solutions and new, more sustainable health care models. Technology centers around the individual, allowing for greater autonomy and control in health issues and access to tailored information and customized health behavior interventions. While this offers good opportunities for both public health impact and improved well-being at individual levels, it also emphasizes the need for properly designed e-health models firmly based on scientific principles and adequate theoretical frameworks. Consequently, this project aims to design an interactive tool utilizing an interdisciplinary approach combining motivational theory with the fields of information technology and business model innovation. In collaboration with two companies from the e-health industry, the purpose is to design, apply and evaluate a person-centered interactive prototype for maintainable and self-determined exercise motivation.
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| 23. |
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| 24. |
- Weman Josefsson, Karin, 1975-, et al.
(författare)
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Application of self-determination theory in the e-health industry – promoting sustainable exercise motivation
- 2015
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Ingår i: Proceeding. - Bern : University of Bern. - 9783033051294 ; , s. 372-372
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Konferensbidrag (refereegranskat)abstract
- Developing tailored digital interventions for exercise motivation by applying behavioral theory into existing web services in cooperation with the e-health industry could create a mutual base for experience exchange and practical implications. It could also add higher standards to e-health business by providing a scientifically sound and trustworthy foundation for digital solutions. This project aims to design an interactive tool grounded in sport and exercise psychology and combined with the latest expertise from information technology and innovation science, considering e-health industrial requirements and user needs. A main objective is to test the efficacy of using Self-Determination Theory (SDT) in designing, constructing and evaluating an exercise intervention. The digital intervention is based on a literature review mapping exercise motivation related to self-determination theory, complemented by qualitative cross-disciplinary interaction design methodologies, such as qualitative analysis of interviews and contextual observation capturing participant goals, behaviour, preferences, attitudes and frustrations. Intervention contents are essentially autonomy supportive structures, goal-setting support and relapse prevention, self-regulation structures, health information and web links. In February 2015 the intervention prototype will be pilot tested in a randomized controlled trial (RCT), involving existing members and clients (N > 10 000) of two health service companies. Outcomes relate to self-determined exercise motivation (The Basic Psychological Needs in Exercise Scale and The Behavioral Regulation in Exercise Questionnaire-2) and exercise behaviour, measured both by self-report measures (Godin Leisure-Time Exercise Questionnaire) and step counters. The RCT contains three measure points in order to allow advanced analyses of change and mechanisms based on the SDT-process model and motivational profiles. Latent growth curve and structural equation models will primarily be used to analyse data. This pilot study will create a baseline for elaboration into a second phase, were the digital tool will be further developed and longitudinally tested and evaluated over a nine months period. © 2015 University of Bern, Institut of Sport Science
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| 25. |
- Weman Josefsson, Karin, 1975-, et al.
(författare)
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Digital innovations and self-determined exercise motivation : a person-centred perspective
- 2014
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Ingår i: Vitalis – Nordens ledande eHälsomöte 2014. - Göteborg : Vitalis & Sahlgrenska akademin, Göteborgs universitet. ; , s. 22-25
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Konferensbidrag (refereegranskat)abstract
- Health care costs are increasing twice as fast as wealth, making health promotion and development of cost-effective care increasingly important in order to generate sustainable health care solutions. E-health, applications and interactive tools for exercise promotion flourish; but despite this and an overflow of information regarding health benefits of regular physical activity, exercise adherence has proven to be a significant challenge. This article concerns a project aimed to design an interactive tool based on comprehensive knowledge from the field of psychology combined with expertise from information technology and innovation, based on e-health industrial requirements and user needs. The research group will, together with the expertise and infrastructure of the collaborating companies Health Profile Institute AB and Tappa Service AB, support and progress an existing PhD-project on digital interventions in exercise motivation. This will be done by designing; applying and evaluating a person-centred digital intervention prototype for exercise motivation and adherence enhancement based on Self-Determination Theory.
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| 26. |
- Weman Josefsson, Karin, 1975-, et al.
(författare)
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Digital interventions in self-determined exercise motivation – interdisciplinary innovations
- 2015
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Ingår i: ISBNPA 2015. ; , s. 592-592
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Konferensbidrag (refereegranskat)abstract
- Purpose:There is a need for scientifically sound and theory based tools and services in e-health. In this project knowledge from the field of psychology will be complemented by expertise in information technology and innovation science in designing a digital intervention based on Self-determination theory (SDT) aiming to facilitate exercise motivation.Methods:The intervention will be tested by a three wave RCT design in a population of e-health clients (n = 200) in a web based exercise service. Sensors (step counters) and self-reports (Godin Leisure-Time Exercise Questionnaire) will be used to measure objective and subjective exercise behavior while instruments based on SDT (Basic Psychological Needs in Exercise Scale and Behavioral Regulation in Exercise Questionnaire-2 ) will measure factors related to motivation. Advanced mediation variable analyses (MVA) and latent growth curve models (LGCM) will be used to explore motivational processes, changes and profiles in relation to exercise behavior.Expected Results:Based on the SDT process model, it is hypothesized that a (digital) environment supporting basic psychological need satisfaction will facilitate internalization and enhanced self-determined motivation, which in turn will have a positive effect on exercise behavior.Conclusions:Clarifying mechanisms and indirect effects provide knowledge of how intervention effects could be interpreted and understood. Combining high level research design like RCT and advanced analyses as MVA provides valuable contributions to the understanding of theoretical mechanisms of motivation that could inform the tailoring of effective interventions promoting healthy exercise behaviours. In addition, the project might form a prosperous interdisciplinary fusion generating innovative and theory based digital solutions for e-health.
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| 27. |
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| 28. |
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| 29. |
- Wickström, Nicholas, 1970-, et al.
(författare)
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Neural Virtual Sensors — Estimation of Combustion Quality in SI Engines using the Spark Plug
- 1998
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Ingår i: ICANN 98. - London : Springer. - 9783540762638 - 9781447115991 ; , s. 215-220
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Konferensbidrag (refereegranskat)abstract
- We propose two virtual sensors which estimate the location of the pressure peak and the air-fuel ratio from measurements of the ionization current across the spark plug gap.The location of pressure peak virtual sensor produces estimates on a cycle-by-cycle basis for each of the cylinders. These estimates are twice as good as estimates obtained from a linear model.The air-fuel ratio virtual sensor uses the universal exhaust gas oxygen sensor as reference; it produces estimates that are ten times better than estimates obtained from a linear model.
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