Quantifying community mobility after Stroke using mobile phone technology

Megan K. O'Brien; Chaithanya K. Mummidisetty; Xiao Bo; Arun Jayaraman

doi:10.1145/3123024.3123085

Quantifying community mobility after Stroke using mobile phone technology

Megan K. O'Brien, Chaithanya K. Mummidisetty, Xiao Bo, Arun Jayaraman

Physical Medicine and Rehabilitation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

Stroke is a common neurological disorder that can drastically impact mobility - that is, the ability to move in and through one's surroundings. Although rehabilitation programs focus on restoring mobility after stroke, there is no present method for reliably and fully quantifying mobility outside of a clinical setting. Smartphones are ubiquitous wearable sensing systems that can measure community mobility using movement and location tracking. We are currently investigating the ability of smartphone data to characterize post-stroke recovery in a long-term monitoring study (3-6 months). We will evaluate the potential of community mobility features to predict recovery, as determined by traditional clinical assessments. Preliminary results will be available in August 2017. Findings will provide a more objective, complete picture of recovery following stroke as well as the real-world impact of rehabilitation.

Original language	English (US)
Title of host publication	UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
Publisher	Association for Computing Machinery, Inc
Pages	161-164
Number of pages	4
ISBN (Electronic)	9781450351904
DOIs	https://doi.org/10.1145/3123024.3123085
State	Published - Sep 11 2017
Event	2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States Duration: Sep 11 2017 → Sep 15 2017

Publication series

Name	UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers

Other

Other	2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
Country/Territory	United States
City	Maui
Period	9/11/17 → 9/15/17

Funding

This work is funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (RERC-TEAMM grant H133E130020).

Keywords

Activity recognition
GPS
Machine learning
Smartphone
Stroke rehabilitation
Wearable technology

ASJC Scopus subject areas

Software
Hardware and Architecture
Computer Networks and Communications

Access to Document

10.1145/3123024.3123085

Cite this

O'Brien, M. K., Mummidisetty, C. K., Bo, X., & Jayaraman, A. (2017). Quantifying community mobility after Stroke using mobile phone technology. In UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 161-164). (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers). Association for Computing Machinery, Inc. https://doi.org/10.1145/3123024.3123085

O'Brien, Megan K. ; Mummidisetty, Chaithanya K. ; Bo, Xiao et al. / Quantifying community mobility after Stroke using mobile phone technology. UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. pp. 161-164 (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers).

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title = "Quantifying community mobility after Stroke using mobile phone technology",

abstract = "Stroke is a common neurological disorder that can drastically impact mobility - that is, the ability to move in and through one's surroundings. Although rehabilitation programs focus on restoring mobility after stroke, there is no present method for reliably and fully quantifying mobility outside of a clinical setting. Smartphones are ubiquitous wearable sensing systems that can measure community mobility using movement and location tracking. We are currently investigating the ability of smartphone data to characterize post-stroke recovery in a long-term monitoring study (3-6 months). We will evaluate the potential of community mobility features to predict recovery, as determined by traditional clinical assessments. Preliminary results will be available in August 2017. Findings will provide a more objective, complete picture of recovery following stroke as well as the real-world impact of rehabilitation.",

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author = "O'Brien, {Megan K.} and Mummidisetty, {Chaithanya K.} and Xiao Bo and Arun Jayaraman",

note = "Funding Information: This work is funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (RERC-TEAMM grant H133E130020).; 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 ; Conference date: 11-09-2017 Through 15-09-2017",

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O'Brien, MK, Mummidisetty, CK, Bo, X & Jayaraman, A 2017, Quantifying community mobility after Stroke using mobile phone technology. in UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, Association for Computing Machinery, Inc, pp. 161-164, 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017, Maui, United States, 9/11/17. https://doi.org/10.1145/3123024.3123085

Quantifying community mobility after Stroke using mobile phone technology. / O'Brien, Megan K.; Mummidisetty, Chaithanya K.; Bo, Xiao et al.
UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2017. p. 161-164 (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Quantifying community mobility after Stroke using mobile phone technology

AU - O'Brien, Megan K.

AU - Mummidisetty, Chaithanya K.

AU - Bo, Xiao

AU - Jayaraman, Arun

N1 - Funding Information: This work is funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (RERC-TEAMM grant H133E130020).

PY - 2017/9/11

Y1 - 2017/9/11

N2 - Stroke is a common neurological disorder that can drastically impact mobility - that is, the ability to move in and through one's surroundings. Although rehabilitation programs focus on restoring mobility after stroke, there is no present method for reliably and fully quantifying mobility outside of a clinical setting. Smartphones are ubiquitous wearable sensing systems that can measure community mobility using movement and location tracking. We are currently investigating the ability of smartphone data to characterize post-stroke recovery in a long-term monitoring study (3-6 months). We will evaluate the potential of community mobility features to predict recovery, as determined by traditional clinical assessments. Preliminary results will be available in August 2017. Findings will provide a more objective, complete picture of recovery following stroke as well as the real-world impact of rehabilitation.

AB - Stroke is a common neurological disorder that can drastically impact mobility - that is, the ability to move in and through one's surroundings. Although rehabilitation programs focus on restoring mobility after stroke, there is no present method for reliably and fully quantifying mobility outside of a clinical setting. Smartphones are ubiquitous wearable sensing systems that can measure community mobility using movement and location tracking. We are currently investigating the ability of smartphone data to characterize post-stroke recovery in a long-term monitoring study (3-6 months). We will evaluate the potential of community mobility features to predict recovery, as determined by traditional clinical assessments. Preliminary results will be available in August 2017. Findings will provide a more objective, complete picture of recovery following stroke as well as the real-world impact of rehabilitation.

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M3 - Conference contribution

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O'Brien MK, Mummidisetty CK, Bo X, Jayaraman A. Quantifying community mobility after Stroke using mobile phone technology. In UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc. 2017. p. 161-164. (UbiComp/ISWC 2017 - Adjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers). doi: 10.1145/3123024.3123085

Quantifying community mobility after Stroke using mobile phone technology

Abstract

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Funding

Keywords

ASJC Scopus subject areas

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