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Completed

NCT Number: NCT05922865

The Effect of Smart Sensor Combined With APP for Individualized Precise Exercise Training in Long Covid-19

The coronavirus (COVID -19) has rapidly turned into a global pandemic. For patients diagnosed with COVID-19, it caused severe damage in the upper respiratory system and systemic complications, including the cardiovascular, mental, nervous, and musculoskeletal system. Previous research has indicated that these subsequent sequelae can reduce quality of life. (A. W. Wong et al., 2020) Studies have indicated that exercise training is beneficial to improve blood pressure, reduce cardiovascular factors, reduce complications, and relieve depression (J. Galloza et al., 2017) However, the current international research on the benefits of exercise rehabilitation and the improvement of quality of life in patients who have been infected with COVID-19 is still lacking. Under the international epidemic, it is pointed out that the importance of telerehabilitation has also been advocated worldwide. Previous systematic review indicated that no matter it is nervous, muscular or cardiac system disease, the efficacy of telerehabilitation is superior to face-to-face rehabilitation. The purpose of this study is to compare the effect between the intervention of KNEESUP smart knee assistive device, and the health education in routine outpatient after diagnosis of Long Covid-19.

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Key information

About this study

The purpose of KNEESUP measuring equipment used in this research is to improve the recovery rate and reduce the sequelae after treatment. KNEESUP connects the subjects and researchers through technologies such as IoT and AI. The evaluation of the rehabilitation results can be presented as a data chart, and the treatment effects are also clearly presented.

For the subject, the subject puts on KNEESUP knee pads in a long sitting position, bends the knees about 30 degrees, aligns the position of the knee pad circle with the bone, and uses the strap on the lower side, upper side, and the knee pads. After wearing, press and hold the sensor on the outer side of the knee pad for 3 seconds, and then open the mobile app. After the hardware setting and connection are completed, the evaluation and exercise can begin.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • symptoms last at least one month after recovery
  • without physical impairment
  • understood verbal or non-verbal communication
  • normal cognitive function
  • were willing to participate in the study and accept random allocation

Exclusion criteria

  • diagnosed with transient ischemic attack or stroke
  • had neuromuscular injury or surgery in the lower limbs in the past six months
  • had heart rhythm regulator
  • hospitalized during training
  • had aggravated symptoms due to infection again
  • had participated in other clinical trials or received other alternative treatments

Treatment and study plan

KNEESUP smart knee assistive device + KNEESUP care APP

Device

In KNEESUP smart knee assistive device + KNEESUP care APP group, participants used the KNEESUP intelligent knee assistive device. Participants wore a knee brace with a sensor module on one side of the leg, the sensor could connect with the KNEESUP care APP which were installed in participant's mobile phone. The APP was designed with an individualized exercise program and the knee brace sensor could detect the action moment of the participants during exercise. This equipment could help the participants to achieve professional-level home rehabilitation.

Healthy consulation

Behavioral

In Healthy consulation group, participants received routine outpatient health education.

Primary outcomes

  1. Aerobic capacity (VO2 max in ml/kg/min )

    Time frame: baseline, 12 weeks

    Maximal VO2 during testing, also means aerobic capacity

  2. Anaerobic Threshold (mL/kg/min)

    Time frame: baseline, 12 weeks

    Anaerobic Threshold (AT) refers to the exercise intensity at which lactate begins to accumulate in the blood at a faster rate than it can be removed. It represents a transition point between predominantly aerobic metabolism (using oxygen) and increased anaerobic metabolism (without sufficient oxygen).

  3. Working load in watt

    Time frame: baseline, 12 weeks

    Maximal Working load during testing

  4. Breathing reserve (ml/kg/min)

    Time frame: baseline, 12 weeks

    A measure used during cardiopulmonary exercise testing (CPET) to assess how much of a person's maximum ventilatory capacity is unused at peak exercise. It reflects the difference between the maximum voluntary ventilation (MVV) and the minute ventilation (VE) reached during exercise.

  5. Rest Heart rate in beat/min

    Time frame: baseline, 12 weeks

    Resting heart rate during exercise testing

  6. O2 pulse in ml/beat

    Time frame: baseline, 12 weeks

    It means the heart pumps O2 volume by each heart beat, and also means left ventricle function.

  7. Systolic blood pressure in mm Hg

    Time frame: baseline, 12 weeks

    The resting blood pressure during exercise testing

  8. Diastolic blood pressure in mm Hg

    Time frame: baseline, 12 weeks

    The resting blood pressure during exercise testing

  9. VE/VCO2 slope

    Time frame: baseline, 12 weeks

    The ventilation/ perfusion abnormalities (VE/VCO2) is measured by graded exercise testing.The change in VE/VCO2 was calculated as the value at 12 weeks minus the value at baseline. A lower VE/VCO2 ratio indicates better ventilatory efficiency and reduced ventilation/perfusion abnormalities.

  10. Heart rate recovery

    Time frame: baseline, 12 weeks

    The heart rate recovery is measured by graded exercise testing, including 1 minute and 2 minute recovery.

    The change in heart rate recovery was calculated as the difference between heart rate recovery at 12 weeks and heart rate recovery at baseline. A decrease of < 12 or 22 beats per minute in 1- or 2- min heart rate recovery, respectively, indicates an elevated risk of mortality. A faster heart rate recovery indicates better cardiovascular fitness and autonomic regulation.

  11. FVC (L/min)

    Time frame: baseline, 12 weeks

    The total amount of air exhaled (mL) during a forced expiratory volume test will be measured by spirometry. The change in FVC was calculated as the value at 12 weeks minus the value at baseline. A higher FVC indicates better lung function.

  12. FEV1 (L/min)

    Time frame: baseline, 12 weeks

    The amount of air exhaled (mL) during the first second during a forced expiratory volume test will be measured by spirometry. The change in FEV1 was calculated as the value at 12 weeks minus the value at baseline. A higher FEV1 indicates better lung function.

  13. FEV1/FVC (%)

    Time frame: baseline, 12 weeks

    The measured FEV1 is divided by the measured FVC. he change in FEV1/FVC was calculated as the value at 12 weeks minus the value at baseline. A higher FEV1/FVC ratio generally indicates better lung function, while a lower ratio suggests airflow limitation.

  14. Gait: Step length (m) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  15. Gait: Speed (m/s) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  16. Gait: Cadence (steps per minute) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  17. Gait: Left gait cycle (sec) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  18. Gait: Right gait cycle (sec) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  19. Gait: Turn around time (sec) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  20. Gait: Stand up time (sec) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  21. Gait: Total walking time (sec) through Time Up and Go Test

    Time frame: baseline, 12 weeks

    Analysis software was evaluated using METASENS. Begin by having the participants sit back in a standard arm chair and identify a 3 meters line on the floor. Participants walk forward three meters at the usual speed, turn around and return to the chair before sitting down. The METASENS evaluation analysis software calculates the step length (m), speed (m/s), cadence (steps per minute), left/right gait cycle (sec), left/right knee flexion angle (deg), left/right foot contact extension angle (deg), turn around time (sec), stand up time (sec), total walking time (sec).

  22. Long COVID symptoms

    Time frame: baseline, 12 weeks

    A simple checklist to record Long COVID symptoms. Symptoms that persisted or were newly developed after acute infection were documented as sequelae. Symptoms included fatigue, shortness of breath, cognitive dysfunction (referred to as "brain fog"), chest pain, cough, dizziness, headache, sleep disturbances, palpitations, depression/anxiety, and olfactory dysfunction.

Secondary outcomes

  1. Quality of life (scores)

    Time frame: baseline, 12 weeks

    The Taiwanese version of the WHO Quality of Life-BREF (WHOQOL-BREF) with good validity and reliability includes the globally standardized WHOQOL-BREF with 26 items and an additional two locally developed items, making a total of 28 items. It consists of two single-facet items measuring overall quality of life and general health and four domains, including physical (7 items), psychological (6 items), social (4 items), and environmental (9 items) domains. The two additional items are being respected/accepted facet in the social domain and eating/food facet in the environment domain, respectively. The participants rated all items on a scale of 1-5, with higher scores reflecting a greater quality of life. Domain scores were derived by multiplying the mean of the facet scores within each domain by a scaling factor of 4, resulting in potential domain scores ranging from 4 to 20.

  2. Sleeping Quality (scores)

    Time frame: baseline, 12 weeks

    Symptoms of sleeping quality will be assessed using Pittsburgh Sleeping Index. The content is aimed at the sleep conditions of the subjects, including seven items including personal self-evaluation of sleep quality, sleep latency, sleep hours, sleep efficiency, sleep disturbance, drug use and daytime dysfunction. Each item is calculated by the Likert four-point method, 0-3 points, the total score ranges from 0-21 points, and the higher the score, the worse the sleep quality. (MORGAN, DALLOSSO, EBRAHIM, ARIE, & Fentem, 1988; Tang Zhenqing et al., 2014).

  3. Body composition: Body weight (kg)

    Time frame: baseline, 12 weeks

    The InBody device is a bioelectrical impedance analysis (BIA) system designed to assess body composition in a non-invasive, rapid, and reliable manner. It quantifies key components such as skeletal muscle mass, body fat mass, total body water, and visceral fat area.

  4. Body composition: Body fat (%)

    Time frame: baseline, 12 weeks

    The InBody device is a bioelectrical impedance analysis (BIA) system designed to assess body composition in a non-invasive, rapid, and reliable manner. It quantifies key components such as skeletal muscle mass, body fat mass, total body water, and visceral fat area.

  5. Body composition: Lean mass weight (kg)

    Time frame: baseline, 12 weeks

    The InBody device is a bioelectrical impedance analysis (BIA) system designed to assess body composition in a non-invasive, rapid, and reliable manner. It quantifies key components such as skeletal muscle mass, body fat mass, total body water, and visceral fat area.

Sponsors and collaborators

Lead sponsor

Shang-Lin Chiang

Other

Registry information

Official study title

Tri-service General Hospital, National Defence Medical Center, Taipei, Taiwan

Important dates

Study start
2023
Primary completion
2024
Study completion
2024
First posted
Jun 28, 2023
Registry last updated
Apr 27, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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