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Cardiopulmonary Training in the Victims With Multiple Morbidities by Application of Novel Heart Rate Sensing Clothes

S

Shang-Lin Chiang

Status

Enrolling

Conditions

Multiple Morbidities
Degeneration Muscle
Heart; Complications

Treatments

Behavioral: Healthy consultation
Device: E-clothes

Study type

Interventional

Funder types

Other

Identifiers

NCT04022590
Smart clothes

Details and patient eligibility

About

Investigators assume that the wearable clothes can be applied to home-based health care and integrated into a case management model through telehealthcare. While prior to complete the case management, the feasibility should be tested and evaluate its reliability and validity of the physical information collected from the clothes. Therefore, investigators try to conduct a feasibility study to evaluate the reliability and validity of the exercise heart rate sensing e-clothes and after that, investigators will incorporate this wearable clothes to home-based exercise training as one of the major components in our case management model.

Full description

Easy-to-use and service touch points allow patients/ users to realize the value and status of their physiological functions/ parameters based on their evidence is important. According to the U.S. survey, 90% of people can change their lifestyle behaviors, improve their personal health awareness, achieve holistic health care and improve their quality of life due to "Quantify Self". Therefore, a broader health care system, health consumption services or ecological system has been building to integrate health care resources, extend health care services from hospital to communities and individual' homes. When people consume in their daily life, immediate public health guidance or professional intervention can be offered at the same time, not only can effectively maintain individuals' health, early detection of possible physiological signs/ parameters, can also delay the progression of the disease and reduce the burden of first-line health care workers. Therefore, it is the era of smart healthcare that provides a health service platform with APPs(Applications) to provide personalized integrated medical services. However, in order to monitor or evaluate the effect of treatment (i.e., exercise training) still needs to be provided through the actual feedback of individual physiological data.

Clothes with smart function which is able to connect with social media and APPs has been promoting and marketing as smart sports or lifestyle-monitor goods, such as exercise-related physical parameters and sleep quality quantifying. Sleep physiology information collected through the clothes including degree and quality of sleep can be recorded and transmitted to the remote health system via APP and cloud service platform. On this cloud platform, health information can exchange with clinician's physicians, offering advises for users to whether to go to the hospital for further examination.

Enrollment

60 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • more than two chronic disease.(multiple morbidity)
  • able to speak and understand Mandarin
  • able to walk without assistance
  • able to use smart phones and understand how to use the e-clothes and related app
  • agreed to be randomized to one of the two groups

Exclusion criteria

  • a history of cancer
  • confirmed psychiatric disease
  • inability to participate due to comorbid neurological and musculoskeletal conditions
  • a history of arrhythmia

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

60 participants in 2 patient groups

E-clothes
Experimental group
Description:
The participants with E-clothes do aerobic training at home
Treatment:
Behavioral: Healthy consultation
Device: E-clothes
Home exercise
Active Comparator group
Description:
The participants with healthy consultation do aerobic training at home.
Treatment:
Behavioral: Healthy consultation

Trial contacts and locations

1

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Central trial contact

Shang-Lin Chiang, PhD; Liang-Hsuan Lu, MS

Data sourced from clinicaltrials.gov

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