MOPS -- A feasibility Study for working with GPS and sensor data in a medical context

Background Patients with head and neck cancer (HNC) experience severe side effects during radiotherapy (RT). Ongoing technological advances in wearable biometric sensors allow for the collection of objective data (eg, physical activity and heart rate), which might, in the future, help detect and counter side effects before they become severe. A smartwatch such as the Apple Watch allows for objective data monitoring outside the hospital with minimal effort from the patient. To determine whether such tools can be implemented in the oncological setting, feasibility studies are needed. Objective This protocol describes the design of the OncoWatch 1.0 feasibility study that assesses the adherence of patients with HNC to an Apple Watch during RT. Methods A prospective, single-cohort trial will be conducted at the Department of Oncology, Rigshospitalet (Copenhagen, Denmark). Patients aged ≥18 years intended for primary or postoperative curatively intended RT for HNC will be recruited. Consenting patients will be asked to wear an Apple Watch on the wrist during and until 2 weeks after RT. The study will include 10 patients. Data on adherence, data acquisition, and biometric data will be collected. Demographic data, objective toxicity scores, and hospitalizations will be documented. Results The primary outcome is to determine if it is feasible for the patients to wear a smartwatch continuously (minimum 12 hours/day) during RT. Furthermore, we will explore how the heart rate and physical activity change over the treatment course. Conclusions The study will assess the feasibility of using the Apple Watch for home monitoring of patients with HNC. Our findings may provide novel insights into the patient’s activity levels and variations in heart rate during the treatment course. The knowledge obtained from this study will be essential for further investigating how biometric data can be used as part of symptom monitoring for patients with HNC. Trial Registration ClinicalTrials.gov NCT04613232; https://clinicaltrials.gov/ct2/show/NCT04613232 International Registered Report Identifier (IRRID) PRR1-10.2196/26096

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Using Biometric Sensor Data to Monitor Cancer Patients During Radiotherapy: Protocol for the OncoWatch Feasibility Study (Preprint)

10.2196/preprints.26096 ◽

2020 ◽

Author(s):

Cecilie Holländer-Mieritz ◽

Ivan R Vogelius ◽

Claus A Kristensen ◽

Allan Green ◽

Judith L Rindum ◽

...

Keyword(s):

Physical Activity ◽

Heart Rate ◽

Side Effects ◽

Feasibility Study ◽

Demographic Data ◽

Home Monitoring ◽

Sensor Data ◽

Activity Levels ◽

Objective Data ◽

Biometric Data

BACKGROUND Patients with head and neck cancer (HNC) experience severe side effects during radiotherapy (RT). Ongoing technological advances in wearable biometric sensors allow for the collection of objective data (eg, physical activity and heart rate), which might, in the future, help detect and counter side effects before they become severe. A smartwatch such as the Apple Watch allows for objective data monitoring outside the hospital with minimal effort from the patient. To determine whether such tools can be implemented in the oncological setting, feasibility studies are needed. OBJECTIVE This protocol describes the design of the OncoWatch 1.0 feasibility study that assesses the adherence of patients with HNC to an Apple Watch during RT. METHODS A prospective, single-cohort trial will be conducted at the Department of Oncology, Rigshospitalet (Copenhagen, Denmark). Patients aged ≥18 years intended for primary or postoperative curatively intended RT for HNC will be recruited. Consenting patients will be asked to wear an Apple Watch on the wrist during and until 2 weeks after RT. The study will include 10 patients. Data on adherence, data acquisition, and biometric data will be collected. Demographic data, objective toxicity scores, and hospitalizations will be documented. RESULTS The primary outcome is to determine if it is feasible for the patients to wear a smartwatch continuously (minimum 12 hours/day) during RT. Furthermore, we will explore how the heart rate and physical activity change over the treatment course. CONCLUSIONS The study will assess the feasibility of using the Apple Watch for home monitoring of patients with HNC. Our findings may provide novel insights into the patient’s activity levels and variations in heart rate during the treatment course. The knowledge obtained from this study will be essential for further investigating how biometric data can be used as part of symptom monitoring for patients with HNC. CLINICALTRIAL ClinicalTrials.gov NCT04613232; https://clinicaltrials.gov/ct2/show/NCT04613232 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/26096

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Feasibility study on sensor data fusion for the CP-140 aircraft: fusion architecture analyses

10.1117/12.217707 ◽

1995 ◽

Author(s):

Elisa Shahbazian

Keyword(s):

Data Fusion ◽

Feasibility Study ◽

Sensor Data ◽

Sensor Data Fusion

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Collecting Symptoms and Sensor Data With Consumer Smartwatches (the Knee OsteoArthritis, Linking Activity and Pain Study): Protocol for a Longitudinal, Observational Feasibility Study

JMIR Research Protocols ◽

10.2196/10238 ◽

2019 ◽

Vol 8 (1) ◽

pp. e10238 ◽

Cited By ~ 6

Author(s):

Anna L Beukenhorst ◽

Matthew J Parkes ◽

Louise Cook ◽

Rebecca Barnard ◽

Sabine N van der Veer ◽

...

Keyword(s):

Knee Osteoarthritis ◽

Feasibility Study ◽

Study Protocol ◽

Sensor Data

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Feasibility Study on Online Guiding of Industrial Robot by Experimentally Created Force/Torque Map for Peg-in-Hole Assembling

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.799-800.1074 ◽

2015 ◽

Vol 799-800 ◽

pp. 1074-1077

Author(s):

Mustafa Waad Abdullah ◽

Hubert Roth ◽

Michael Weyrich ◽

Jürgen Wahrburg ◽

Bashra Kadhim Oleiwi

Keyword(s):

Real Time ◽

Feasibility Study ◽

Industrial Robot ◽

Sensor Data ◽

Assembly Task

The experiment carried in this paper aims to study the feasibility of controlling an industrial robot to carry Peg-in-Hole assembling task using what called a Force/Torque Map. This type of control is based on real-time F/T sensor data during contact between the peg and the hole. The F/T Map presents the data acquired during previous attempts of the assembly task.

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