| 1. |
- 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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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- 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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| 6. |
- 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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| 7. |
- 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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| 8. |
- 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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| 9. |
- 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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| 10. |
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