Jog falls: A pervasive healthcare platform for diabetes management

Lama Nachman; Amit Baxi; Sangeeta Bhattacharya; Vivek Darera; Piyush Deshpande; Nagaraju Kodalapura; Vincent Mageshkumar; Satish Rath; Junaith Shahabdeen; Raviraja Acharya

doi:10.1007/978-3-642-12654-3_6

Jog falls: A pervasive healthcare platform for diabetes management

Lama Nachman^*
, Amit Baxi
, Sangeeta Bhattacharya
, Vivek Darera
, Piyush Deshpande
, Nagaraju Kodalapura
, Vincent Mageshkumar
, Satish Rath
, Junaith Shahabdeen
, Raviraja Acharya

^*Corresponding author for this work

Department of Medicine, Kasturba Medical College, Manipal

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

50 Citations (Scopus)

Abstract

This paper presents Jog Falls, an end to end system to manage diabetes that blends activity and energy expenditure monitoring, diet-logging, and analysis of health data for patients and physicians. It describes the architectural details, sensing modalities, user interface and the physician's backend portal. We show that the body wearable sensors accurately estimate the energy expenditure across a varied set of active and sedentary states through the fusion of heart rate and accelerometer data. The GUI ensures continuous engagement with the patient by showing the activity goals, current and past activity states and dietary records along with its nutritional values. The system also provides a comprehensive and unbiased view of the patient's activity and food intake trends to the physician, hence increasing his/her effectiveness in coaching the patient. We conducted a user study using Jog Falls at Manipal University, a leading medical school in India. The study involved 15 participants, who used the system for 63 days. The results indicate a strong positive correlation between weight reduction and hours of use of the system.

Original language	English
Title of host publication	Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings
Pages	94-111
Number of pages	18
Volume	6030 LNCS
DOIs	https://doi.org/10.1007/978-3-642-12654-3_6
Publication status	Published - 18-06-2010
Event	8th International Conference on Pervasive Computing, Pervasive 2010 - Helsinki, Finland Duration: 17-05-2010 → 20-05-2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6030 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Pervasive Computing, Pervasive 2010
Country/Territory	Finland
City	Helsinki
Period	17-05-10 → 20-05-10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-12654-3_6

Cite this

Nachman, L., Baxi, A., Bhattacharya, S., Darera, V., Deshpande, P., Kodalapura, N., Mageshkumar, V., Rath, S., Shahabdeen, J., & Acharya, R. (2010). Jog falls: A pervasive healthcare platform for diabetes management. In Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings (Vol. 6030 LNCS, pp. 94-111). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6030 LNCS). https://doi.org/10.1007/978-3-642-12654-3_6

Nachman, Lama ; Baxi, Amit ; Bhattacharya, Sangeeta et al. / Jog falls : A pervasive healthcare platform for diabetes management. Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings. Vol. 6030 LNCS 2010. pp. 94-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper presents Jog Falls, an end to end system to manage diabetes that blends activity and energy expenditure monitoring, diet-logging, and analysis of health data for patients and physicians. It describes the architectural details, sensing modalities, user interface and the physician's backend portal. We show that the body wearable sensors accurately estimate the energy expenditure across a varied set of active and sedentary states through the fusion of heart rate and accelerometer data. The GUI ensures continuous engagement with the patient by showing the activity goals, current and past activity states and dietary records along with its nutritional values. The system also provides a comprehensive and unbiased view of the patient's activity and food intake trends to the physician, hence increasing his/her effectiveness in coaching the patient. We conducted a user study using Jog Falls at Manipal University, a leading medical school in India. The study involved 15 participants, who used the system for 63 days. The results indicate a strong positive correlation between weight reduction and hours of use of the system.",

author = "Lama Nachman and Amit Baxi and Sangeeta Bhattacharya and Vivek Darera and Piyush Deshpande and Nagaraju Kodalapura and Vincent Mageshkumar and Satish Rath and Junaith Shahabdeen and Raviraja Acharya",

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Nachman, L, Baxi, A, Bhattacharya, S, Darera, V, Deshpande, P, Kodalapura, N, Mageshkumar, V, Rath, S, Shahabdeen, J & Acharya, R 2010, Jog falls: A pervasive healthcare platform for diabetes management. in Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings. vol. 6030 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6030 LNCS, pp. 94-111, 8th International Conference on Pervasive Computing, Pervasive 2010, Helsinki, Finland, 17-05-10. https://doi.org/10.1007/978-3-642-12654-3_6

Jog falls: A pervasive healthcare platform for diabetes management. / Nachman, Lama; Baxi, Amit; Bhattacharya, Sangeeta et al.
Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings. Vol. 6030 LNCS 2010. p. 94-111 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6030 LNCS).

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

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T2 - 8th International Conference on Pervasive Computing, Pervasive 2010

AU - Nachman, Lama

AU - Baxi, Amit

AU - Bhattacharya, Sangeeta

AU - Darera, Vivek

AU - Deshpande, Piyush

AU - Kodalapura, Nagaraju

AU - Mageshkumar, Vincent

AU - Rath, Satish

AU - Shahabdeen, Junaith

AU - Acharya, Raviraja

PY - 2010/6/18

Y1 - 2010/6/18

N2 - This paper presents Jog Falls, an end to end system to manage diabetes that blends activity and energy expenditure monitoring, diet-logging, and analysis of health data for patients and physicians. It describes the architectural details, sensing modalities, user interface and the physician's backend portal. We show that the body wearable sensors accurately estimate the energy expenditure across a varied set of active and sedentary states through the fusion of heart rate and accelerometer data. The GUI ensures continuous engagement with the patient by showing the activity goals, current and past activity states and dietary records along with its nutritional values. The system also provides a comprehensive and unbiased view of the patient's activity and food intake trends to the physician, hence increasing his/her effectiveness in coaching the patient. We conducted a user study using Jog Falls at Manipal University, a leading medical school in India. The study involved 15 participants, who used the system for 63 days. The results indicate a strong positive correlation between weight reduction and hours of use of the system.

AB - This paper presents Jog Falls, an end to end system to manage diabetes that blends activity and energy expenditure monitoring, diet-logging, and analysis of health data for patients and physicians. It describes the architectural details, sensing modalities, user interface and the physician's backend portal. We show that the body wearable sensors accurately estimate the energy expenditure across a varied set of active and sedentary states through the fusion of heart rate and accelerometer data. The GUI ensures continuous engagement with the patient by showing the activity goals, current and past activity states and dietary records along with its nutritional values. The system also provides a comprehensive and unbiased view of the patient's activity and food intake trends to the physician, hence increasing his/her effectiveness in coaching the patient. We conducted a user study using Jog Falls at Manipal University, a leading medical school in India. The study involved 15 participants, who used the system for 63 days. The results indicate a strong positive correlation between weight reduction and hours of use of the system.

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M3 - Conference contribution

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SN - 9783642126536

VL - 6030 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 94

EP - 111

BT - Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings

Y2 - 17 May 2010 through 20 May 2010

ER -

Nachman L, Baxi A, Bhattacharya S, Darera V, Deshpande P, Kodalapura N et al. Jog falls: A pervasive healthcare platform for diabetes management. In Pervasive Computing - 8th International Conference, Pervasive 2010, Proceedings. Vol. 6030 LNCS. 2010. p. 94-111. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-12654-3_6

Jog falls: A pervasive healthcare platform for diabetes management

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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