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Wickström, NicholasORCID iD iconorcid.org/0000-0002-4143-2948
Publications (10 of 45) Show all publications
Khandelwal, S. & Wickström, N. (2018). Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations. Gait & Posture, 59, 278-285
Open this publication in new window or tab >>Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations
2018 (English)In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 59, p. 278-285Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2018
Keywords
Gait event, Inertial sensor, sensor placement, wavelet transform, domain knowledge, gait database
National Category
Signal Processing
Identifiers
urn:nbn:se:hh:diva-34639 (URN)10.1016/j.gaitpost.2017.07.030 (DOI)2-s2.0-85026637369 (Scopus ID)
Funder
Knowledge Foundation
Note

Funding: The Knowledge Foundation, Sweden and Promobilia Foundation, Sweden

Available from: 2017-07-21 Created: 2017-07-21 Last updated: 2018-03-26Bibliographically approved
Khandelwal, S. & Wickström, N. (2017). Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database. Gait & Posture, 51, 84-90
Open this publication in new window or tab >>Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database
2017 (English)In: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 51, p. 84-90Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2017
Keywords
gait events, gait event detection, accelerometer, inertial sensor, gait database, gait dataset, Heel Strike, Toe Off
National Category
Signal Processing
Identifiers
urn:nbn:se:hh:diva-32110 (URN)10.1016/j.gaitpost.2016.09.023 (DOI)000390463000015 ()27736735 (PubMedID)2-s2.0-84991511975 (Scopus ID)
Funder
Knowledge Foundation
Note

This study was supported in part by the Knowledge Foundation, Sweden.

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-03-26Bibliographically approved
Bentes, J., Khandelwal, S., Carlsson, H., Kärrman, M., Svensson, T. & Wickström, N. (2017). Novel System Architecture for Online Gait Analysis. In: : . Paper presented at 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jeju Island, South Korea, July 11-15, 2017.
Open this publication in new window or tab >>Novel System Architecture for Online Gait Analysis
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2017 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

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.

Keywords
Integrated wearable and portable systems, Physiological monitoring - Modeling and analysis, Physiological monitoring - Novel methods
National Category
Communication Systems
Identifiers
urn:nbn:se:hh:diva-34302 (URN)
Conference
39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jeju Island, South Korea, July 11-15, 2017
Available from: 2017-06-22 Created: 2017-06-22 Last updated: 2018-10-31Bibliographically approved
Khandelwal, S. & Wickström, N. (2016). Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge into Time-Frequency Analysis. IEEE transactions on neural systems and rehabilitation engineering, 24(12), 1363-1372
Open this publication in new window or tab >>Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge into Time-Frequency Analysis
2016 (English)In: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 24, no 12, p. 1363-1372Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Press, 2016
Keywords
accelerometer, gait analysis, inertial sensors, morlet, principles of gait, stride parameters, wavelet transform
National Category
Signal Processing
Identifiers
urn:nbn:se:hh:diva-30468 (URN)10.1109/TNSRE.2016.2536278 (DOI)000390559600010 ()26955043 (PubMedID)2-s2.0-85006253692 (Scopus ID)
Available from: 2016-03-04 Created: 2016-03-04 Last updated: 2018-03-26Bibliographically approved
Weman Josefsson, K., Ebbesson, E., Halila, F., Johnson, U., Lund, J., Wickström, N. & Wärnestål, P. (2015). Application of self-determination theory in the e-health industry – promoting sustainable exercise motivation. In: Olivier Schmid & Roland Seiler (Ed.), Proceeding: 14th European Congress of Sport Psychology: Sport Psychology: Theories and Applications for Performance, Health and Humanity: 14-19 July 2015, Bern, Switzerland. Paper presented at 14th European Congress of Sport Psychology, FEPSAC 2015, Bern, Switzerland, July 14-19th, 2015 (pp. 372-372). Bern: University of Bern
Open this publication in new window or tab >>Application of self-determination theory in the e-health industry – promoting sustainable exercise motivation
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2015 (English)In: Proceeding: 14th European Congress of Sport Psychology: Sport Psychology: Theories and Applications for Performance, Health and Humanity: 14-19 July 2015, Bern, Switzerland / [ed] Olivier Schmid & Roland Seiler, Bern: University of Bern , 2015, p. 372-372Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

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 

Place, publisher, year, edition, pages
Bern: University of Bern, 2015
National Category
Psychology
Identifiers
urn:nbn:se:hh:diva-29601 (URN)978-3-033-05129-4 (ISBN)
Conference
14th European Congress of Sport Psychology, FEPSAC 2015, Bern, Switzerland, July 14-19th, 2015
Funder
Knowledge Foundation
Available from: 2015-10-12 Created: 2015-10-12 Last updated: 2018-07-05Bibliographically approved
Weman-Josefsson, K. A., Halila, F., Johnson, U., Wickström, N. & Wärnestål, P. (2015). Digital Innovations and Self-determined exercise motivation: an interdisciplinary approach. In: Proceedings of The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC March 2015. Orlando, Florida.: . Paper presented at The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2015, Orlando, Florida, United States, March 10-13, 2015.
Open this publication in new window or tab >>Digital Innovations and Self-determined exercise motivation: an interdisciplinary approach
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2015 (English)In: Proceedings of The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC March 2015. Orlando, Florida., 2015Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

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.

Keywords
Health technology, exercise, RCT, motivation, self-determination theory
National Category
Social Sciences
Identifiers
urn:nbn:se:hh:diva-28326 (URN)2-s2.0-85027213737 (Scopus ID)
Conference
The 6th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2015, Orlando, Florida, United States, March 10-13, 2015
Available from: 2015-05-25 Created: 2015-05-25 Last updated: 2018-08-27Bibliographically approved
Weman Josefsson, K., Halila, F., Johnson, U., Wickström, N. & Wärnestål, P. (2015). Digital interventions in self-determined exercise motivation – interdisciplinary innovations. In: ISBNPA 2015: Advancing Behavior Change Science : 3rd – 6th June 2015: Abstract Book. Paper presented at ISBNPA 2015 - Conference for International Society for Behavioral Nutrition and Physical Activity, Advancing Behavior Change Science, 3rd - 6th June, 2015, Edinburgh, Scotland (pp. 592-592).
Open this publication in new window or tab >>Digital interventions in self-determined exercise motivation – interdisciplinary innovations
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2015 (English)In: ISBNPA 2015: Advancing Behavior Change Science : 3rd – 6th June 2015: Abstract Book, 2015, p. 592-592Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

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.

Keywords
self-determination, exercise, innovation, interdisciplinary
National Category
Psychology
Identifiers
urn:nbn:se:hh:diva-29599 (URN)
Conference
ISBNPA 2015 - Conference for International Society for Behavioral Nutrition and Physical Activity, Advancing Behavior Change Science, 3rd - 6th June, 2015, Edinburgh, Scotland
Funder
Knowledge Foundation
Note

Poster P3.116

Available from: 2015-10-12 Created: 2015-10-12 Last updated: 2018-07-05Bibliographically approved
Ourique de Morais, W. & Wickström, N. (2015). Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments. Halmstad: Halmstad University
Open this publication in new window or tab >>Evaluation of Extensibility, Portability and Scalability in a Database-centric System Architecture for Smart Home Environments
2015 (English)Report (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Halmstad: Halmstad University, 2015. p. 14
Keywords
database-centric architecture, smart environments, ambient assisted living, quality attributes
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hh:diva-29141 (URN)
Available from: 2015-08-11 Created: 2015-08-11 Last updated: 2016-03-09Bibliographically approved
Ourique de Morais, W. & Wickström, N. (2014). A lightweight method for detecting sleep-related activities based on load sensing. In: SeGAH 2014: IEEE 3rd International Conference on Serious Games and Applications for Health. Paper presented at IEEE 3rd International Conference on Serious Games and Applications for Health (SeGAH 2014), Rio de Janeiro, Brazil, May 14-16, 2014. Red Hook, NY: Curran Associates, Inc., Article ID 7067080.
Open this publication in new window or tab >>A lightweight method for detecting sleep-related activities based on load sensing
2014 (English)In: SeGAH 2014: IEEE 3rd International Conference on Serious Games and Applications for Health, Red Hook, NY: Curran Associates, Inc., 2014, article id 7067080Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Red Hook, NY: Curran Associates, Inc., 2014
Keywords
Healthcare technology, home monitoring, sensor-based monitoring systems, load sensing, sleep assessment, state machines, bed-exit alarms
National Category
Electrical Engineering, Electronic Engineering, Information Engineering Nursing
Identifiers
urn:nbn:se:hh:diva-26239 (URN)10.1109/SeGAH.2014.7067080 (DOI)000393517600011 ()2-s2.0-84988259056 (Scopus ID)978-1-4799-4823-9 (ISBN)
Conference
IEEE 3rd International Conference on Serious Games and Applications for Health (SeGAH 2014), Rio de Janeiro, Brazil, May 14-16, 2014
Available from: 2014-08-13 Created: 2014-08-13 Last updated: 2017-03-22Bibliographically approved
Ourique de Morais, W., Lundström, J. & Wickström, N. (2014). Active In-Database Processing to Support Ambient Assisted Living Systems. Sensors, 14(8), 14765-14785
Open this publication in new window or tab >>Active In-Database Processing to Support Ambient Assisted Living Systems
2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 8, p. 14765-14785Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Basel: Multidisciplinary Digital Publishing Institute AG, 2014
Keywords
healthcare technology, smart homes, ambient assisted living, database management systems, active databases, in-database processing, data mining
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hh:diva-26238 (URN)10.3390/s140814765 (DOI)000341499900073 ()2-s2.0-84939496768 (Scopus ID)
Note

This article belongs to the Special Issue Select Papers from UCAmI & IWAAL 2013 - the 7th International Conference on Ubiquitous Computing and Ambient Intelligence & the 5th International Workshop on Ambient Assisted Living (UCAmI & IWAAL 2013: Pervasive Sensing Solutions

Available from: 2014-08-13 Created: 2014-08-13 Last updated: 2017-12-05Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-4143-2948

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