KHealth Bariatrics: A Multi-sensory Approach to Support Patient for Post Surgical behaviour

From Knoesis wiki
Jump to: navigation, search

Motivation and Background

Obesity has evolved into a pandemic health problem. According to American Society for Metabolic and Bariatric Surgery (ASMBS), 500 million people all over the world are obese[1]. The data from Centers for Disease Control and Prevention(CDC) shows that more than 36% of adults in the United States have obesity[2]. According to World Health Organization (WHO), 65% of the world’s population lives in countries where the occurrence of death due to overweight and obesity is higher than being underweight[1]. Also, the analysis on the prevalence of obesity shows that it has doubled in more than 70 countries and continuously increased in most other countries since 1980[4]. The disease burden of obesity heeds the attention as it has reached epidemic proportions.

kHealth kit for Bariatrics

Image Source:Center for Disease Control and Prevention

Bariatrics: Challenges and Opportunities

Bariatric surgery is one of the most effective means of treating obesity, resulting in improved obesity related co-morbidities and increased over all life expectancy[3]. But, the weight recidivism post bariatric surgery has been observed in significant proportion of the patients. After surgery, a lifelong commitment to behavioral and dietary modifications is necessary and not always accomplished long term. Hence a strict compliance to the recommended guidelines is necessary to prevent weight regain. Also, aetiologies of weight regain appeared to be multifactorial and overlapping, relating to patient specific factors[3]. The need for continuous monitoring of BMI changes, diet and nutrition intake, physical activity and behavioural changes makes difficult to narrow down to a factor contributing to weight regain. Thus, an organised and systematic framework that monitors the patient continuously and is capable of notifying the clinician whenever there is a deviation from the expected guideline is essential.

kHealth: Knowledge enabled Personalised Digital Healthcare

As the austerity of the diseases grew, the Internet of Medical Things(IoMT) evolved as well. An extensive usage of mobile devices and sensors has been observed lately. Utilizing data from these devices to make timely decisions, realigned the medical domain from reactive medicine to proactive and preventive medicine. The massive amount of diversified data collected from sensors are difficult to analyse and understand manually. kHealth framework is a knowledge-enabled semantic platform that captures the variation in the data and analyse it to produce actionable information[5]. This probabilistic reasoning framework will aid in predicting the detrimental outcome and prevent them.

Director of Kno.e.sis and Professor of Computer Science and Engineering, Dr. Amit Sheth describes the impact of IoT and AI in the healthcare and the paradigm shift that the health domain is going through.

kHealth Bariatrics

kHealth Bariatrics is an effort to bout against weight recidivism post bariatric surgery. The computer scientists working at Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, are collaborating with a bariatric surgeon and a behavioural specialist to bolster weight loss surgery patients for appropriate postsurgical progress. In our mobile personalized digital health solution, we use an Android application coupled with sensors to monitor patient’s compliance with post-surgery progress and motivate patients to have proper follow-ups.

kHealth kit for Bariatrics

The sensors include a wireless weighing machine that automatically sends data to the cloud, activity and sleep monitoring wristband which also measures heart rate, water bottle sensor and pill bottle sensor which prompts the patient for proper intake of water and vitamin pills. Additionally, the android app with its simple questionnaire helps in monitoring the patient’s diet and emotional well-being.


People

  • Co-Investigators
    • Dr. Priti Parikh (Assistant Professor, Dept. of Surgery, Wright State University)
    • Dr. Dene Berman


  • Undergraduate Medical Student, Boonshoft School of Medicine:
    • Sarah Sohail

Contact: Revathy Venkataraman

Related Talks and Presentations

Poster:

Presented at Obesity Week 2017. 34th ASMBS Annual Meeting; 2017 Oct 29- Nov 2; Washington D.C.

ASMBS Poster


Presentation:

Presented at Celebration of Research, Scholarship and Research Activities '17. Wright State University

Institution Review Board (IRB)

Wright State University's Institution Review Board has approved this study on October 17, 2017. The enrollment for the pilot study has begun. The IRB number for this study is OHRP #IRB00000034

Related kHealth Projects


Publications

[1] Sohail S, Venkataramanan R, Jaimini U, Berman D, Parikh P, Sheth A, Shim JK. A Multisensory Approach to Monitor Bariatric Patients’ Postsurgical Behavior and Lessen Weight Recidivism. Poster presented at: Obesity Week 2017. 34th ASMBS Annual Meeting; 2017 Oct 29- Nov 2; Washington D.C.
[2] Venkataramanan , R., Jaimini , U., Sheth , A., Shim , J. K., Parikh , P., & Berman , D. S. (2017). kHealth Bariatrics: A Multisensory approach to monitoring Patient’s Postsurgical Behavior. Presented at: Celebration of Research, Scholarship and Research Activities 2017. Wright State University.


References

[1]"Disease of Obesity". American Society for Bariatric and Metabolic Surgery. Retrieved on Sep 21,2017.
[2]"Adult Obesity Facts". Center for Disease Control and Prevention, 01 Sept 2016. Retrieved on 30 Apr 2017.
[3]Shahzeer Karmali, Balpreet Brar, Xinzhe Shi, Arya M. Sharma, Christopher Gara, Daniel W. Birch. Weight Recidivism Post-Bariatric Surgery: A Systematic Review.(2013) Obesity Surgery 23, 1922-1933.Retrieved on Sep 25,2017.
[4]"Health Effects of Overweight and Obesity in 195 countries over 25 years".(2017). The New England Journal of Medicine, Vol.377.Retrieved on Sep 25,2017.
[5]"kHealth: A knowledge-enabled semantic platform to enhance decision making and improve health, fitness, and well-being". Kno.e.sis. Retrieved on Sep 25,2017.