Resources

• • AutoSense is a mobile sensor suite that is worn, usually clipped, to a respiratory inductive plethysmography (RIP) belt that is itself worn about the participant’s chest (this RIP belt is often simply called a “chest belt”). The sensor unit is connected via wires to the RIP belt and via two-lead electrodes to single-use snap electrode pads, usually comprised of a foam backing, though cloth ECG electrode pads are sometimes used for user comfort (e.g., in cases of sensitive skin). These single-use electrode pads are often replaced once-to-several-times a day depending on adhesion that may be affected by perspiration or physical activity, for example.

• • The Autosense chestband sensors collect data from (1) two-lead electrocardiogram (ECG) measurement of electrical activity from the heart, (2) respiratory inductive plethysmography band for measurement of relative lung volume and breathing rate at the rib cage, and (3) a three-axis accelerometer to assess motion artifacts in the data and provide inferences about physical activity. This unit is small (1’’X2.5’’) and includes a 750 mAh battery that does not require recharging for several days. Data are collected from this unit via streaming sensor measurements via wireless radio connection to a smartphone in real-time.

• • Wristband sensors will be worn on each wrist. Each of these devices includes 3-axis accelerometers and 3-axis gyroscopes, and may include other sensors such as Heart Rate based on reflectance photoplethysmogram (PPG), UV light exposure, and a skin contact sensor. Data are collected from these sensors via wireless radio connection to a smartphone in real-time.

• • The mobile sensor suite will continuously capture mobile sensor data onto the dedicated study smartphone. These data will be stored on the phone’s (encrypted) microSD card, where some preliminary computations to the data will occur (e.g., the computation of stress events from physiological signals). Participants will also use the study smartphones to complete ecological momentary assessment (EMA) surveys and denote self-report events [e.g., where smoking lapses have occurred]. The study smartphone will also automatically record the time and location (geospatial coordinates) for participants at the time of survey completion and during collection of the sensor data streams. [Example language for intervention studies:] Study smartphones will also be used to deliver micro-randomized stress-reduction interventions to the participants. These interventions will be micro-randomized based on the presence/absence of [physiological marker, e.g., stress].

• • Ecological Momentary Assessments (EMAs) are self-reports made on the smartphone throughout the day. Prompts will be delivered randomly in each of three four-hour blocks from the beginning of the participants’ querying the phone after waking. For example, these blocks may extend from 8am-12pm, 12pm-4pm, and 4pm-8pm, if the participant begins the day at 8am. [In the case of smoking cessation studies:] Planned prompts will ask participants a survey [e.g., of 14-16 questions three times daily] about smoking usage since last prompt, feelings, tobacco craving, positive affect, and negative affect ([it is customary to include these questions in a separate document for IRB review:] see attached “Ecological Momentary Assessment Approach” document for details).

• • Periodically during the day, the smartphones will also be transmitting all of the sensor data collected by the phones. These data will be transmitted to a secure, encrypted computational cluster that is managed by the MD2K Center of Excellence at the University of Memphis. These data will be further processed and transformed, using the computational infrastructure of the cluster.

• • Participants may experience slight initial discomfort while wearing the sensors, such as minor skin irritations. However, the AutoSense chest and wrist band sensors have been used in multiple field studies with over 100 participants, and no significant skin irritation has been reported. Therefore, we assess the severity of the discomfort and irritation of wearing the sensors to be low. If the irritation persists to a point where the participant no longer wishes to participate the irritation is entirely reversible once the participant removes the sensors.

• • As with any electrical device, the sensors can theoretically cause electric shocks. Electrical shocks can be a health concern with certain health conditions (e.g., heart conditions that require a pacemaker). However, the probability of a participant experiencing even minor electrical shocks is negligible. High impedance circuitry is used to limit current flow, even in the case of external events (e.g., through physical breaking of the sensor board or shorting of the battery leads). AutoSense has been used in several previously completed studies on different populations; no adverse events have been reported or observed from the use or wearing of AutoSense.

• • All sensors in the wristband sensor devices are commonly used in mobile phone and other activity monitors, and pose minimal risks to participants. Previous studies with wristband sensors have indicated that after a brief adjustment period, the majority of the participants adjusted to wearing the bands and did not find them to be intrusive or restraining. We expect that the wristband sensors, which have precedent of prior use in a research study or have otherwise been designed for everyday wear, will elicit similar acceptability among the participants in this study.

• •  Location data (GPS) collected from the participants has the risk of identifying the participant by depicting his/her exact location at a given time during the study. These data will also depict every location the participant has been, which may be potentially embarrassing if revealed. However, these data will be kept secure using best practices in data security. Moreover, access to these data will be restricted to authorized investigators and study staff who have IRB approval, have completed training in human subjects protection, and have agreed to uphold the privacy of participants in this study.

• • Administrative, physical, and technical safeguards used to protect the confidentiality of all study data should also be discussed for both mobile and back-end platforms. As an example for MD2K studies, phones are encrypted and managed using mobile device management software that allows for the remote wiping of devices if they are lost or otherwise compromised. Back-end computational hardware is encrypted, firewalled, password protected, and physically secured. Data security is provided by limited access accounts where each individual is explicitly granted access only to the datasets for which they are authorized.

• • Each day that you are wearing AutoSense, you will place a chest belt and electrodes on your chest and a smartwatch on each of your wrists.

• • You will remove the AutoSense chest belt, electrodes, and smartwatches at night while you are sleeping.

• • You should wear the AutoSense chest belt, electrodes, and smartwatches at all times while you are awake, except when you shower, bathe, or swim. The sensors are water-resistant, but are not completely waterproof. Please don’t let the sensors get wet.

• • You should carry the study smartphone with you at all times while wearing the sensors

• • You should always charge the study smartphone and study sensors at night while you are sleeping.

• • The smartphone will gather information about your heart rate, breathing, and activity from the sensors that you will be wearing. This information can be used by the research team to understand when you are feeling stressed, are craving [e.g., drugs, smoking], smoke cigarettes, use certain drugs, or engage in other activities.

• • The smartphone has an internal GPS (GPS stands for Global Positioning System). The GPS will keep track of your location. Your GPS location will only be seen by the researchers who are authorized to look at your data. The purpose of the GPS is not to keep an eye on you, but to help identify locations that are important for the research [examples may be provided].

• • The information collected by the smartphone, including the location ata, will be transferred automatically from your study smartphone to secure data storage [the institution/location of any back-end computational hardware may be listed].

• • At the end of the [study duration] that you wear the sensors, we will ask you to fill out a questionnaire about your experiences wearing the sensors and talk to the researchers about your experience.

IRBs and participants must be informed of how participant data will be managed and shared as a matter of confidentiality. Sample language for several tiers of data sharing (from more restrictive to more permissive) based on the sensitivity of data are presented. Additionally, language describing retention may be flexible, but should also be reasonable and justifiable to the nature of the project and contribution to science. An example of language related to retention of sensor data is provided as well.

• • Study participants will be informed that this research is conducted as a part of the MD2K Center of Excellence. Study participants will be informed that data that may identify them (specifically, GPS) may be shared with other researchers at other institutions who are a part of the MD2K Center of Excellence, if those researchers have a legitimate, IRB-approved question regarding these data. These investigators must provide documentation of their own Institutional Review Board approval or authorization agreement with the [IRB of record] and must agree to maintain the confidentiality of participants’ data before data from this study will be shared with them. Participants will also be informed that their research data that does not include GPS or other (direct or indirect) identifiers may be shared with other (non-MD2K) researchers who have a legitimate research question for which secondary analyses are requested regarding these data.

• • Participants of this research study will be informed of the collaborative nature of the MD2K Center, which includes the following procedures: (1) the secure transmission of study data to the MD2K Center computational cluster at the University of Memphis, (2) that, with approval from their own IRBs and the MD2K Executive Committee, human subjects data may be shared from the computational cluster with other mHealth researchers amongst the 13 institutions that comprise the MD2K Center, and (3) that all investigators must agree to maintain the confidentiality of participants’ data. A listing of the MD2K Center institutions is maintained online at https://www.md2k.org.

• • Raw data, including video and identifiable geolocation (GPS) data, will be available to the study team. We intend to collect video to annotate certain health events, and GPS information to determine whether participants’ geolocation is associated with the presence or absence of certain health behaviors. Raw geolocation data is identifiable, as it can be traced to the exact locations of participants. As such, we will use the GPS data to code for points of interest (POI; i.e., location clusters) that categorically denote the location of participants at a given time (e.g., home, work, school, car, etc.). After the study has been completed, a copy of the dataset will be made that does not contain the video, raw GPS data, or participant codes, yielding a de-identified dataset. Participants will be informed that their de-identified data may be retained and shared with other researchers who are not a part of the research team if those interested researchers submit a research plan to the lead investigator of this study and agree not to share the data with others without the express permission of the lead investigator. Participants will also be given the option to opt into the open sharing of the sensor data that could be downloaded by anyone. These data could be used for any purpose, but would principally be useful for the testing and training of computational models among the wider mHealth community. These data not contain codes or any other identifying elements that could trace back to the identity of the subjects.

• • Study participants will be informed that research data collected about them, including indirectly identifiable GPS (location) traces, will be stored at the [investigator’s institution] until they are no longer useful. It is estimated that the data will possibly be useful for 10 years, but that the data may be useful and may continue to be retained much longer than that.

The following language is an example of how to explain to participants how data may be shared. In this example, the data are to be either coded or de-identified before sharing with other researchers.

This research study is a part of a research collaboration that aims to develop new ways of improving health by using mobile sensor technology. Because of this, we want to save your research data and share it with other researchers who study mobile health. The rest of this section describes how we will use your data and share it with other researchers.

Data security & confidentiality: We will use best practices to prevent unauthorized access to your information. For example, we will make sure that all paper study records are kept in locked areas not accessible to the general public. All electronic study records and data (including video data and GPS) will be kept on computers that are secured with appropriate technical safeguards such as password protection and encryption. This means it will be very difficult for someone to access your information if they do not have permission. We will protect your identity to the extent required by law. However, we cannot guarantee complete secrecy. For example, we are required by law to report evidence of child abuse or neglect. All of your records will be open to inspection by the research study staff, the IRB, other representatives of this institution, and the sponsor of this study: the U.S. Department of Health and Human Services, National Institutes of Health.

How we will use your data: We will link your contact information and your research data (the data collected by all of the questionnaires, study sensors, and the phone) with a code number. A master key that links your name, your contact information, and your code number will be maintained in a separate and secure location from your research data. We will only use your contact information for the purposes of contacting you about this research study, and future research studies if you choose. We will use your research data for scientific progress and for publication of study results. Information that we make public will only be in the form of summaries that make it impossible to tell who the individual participants were.

How we will share your data: The research data that we collect about you in this study may also be shared with other researchers. Some of these researchers may be at other universities/institutions. We will only share information that can’t be used to identify you. GPS data will contain all of the places you have visited during the study. Because of this, GPS data could be used to identify you. We will not share any data that includes your raw location data (GPS) with other researchers. We will use your GPS data to make a code for certain points of interest (POI, also called “clusters”). These POI might say “home,” work,” “school,” “car,” or some other generic code for where you have been at a given time. We will use this code in datasets that we share with other researchers, so that they couldn’t know your exact location while you were in the study.

We will share your research data with these other researchers only after:

1. They describe, in writing, how they will use the data.
2. They agree that they will keep your research data secure. They will agree that only people working on their study will be able to see your research data.

After we finish this study, we will also make a copy of the data that will be stripped of all information that could identify you (including raw location data/GPS and your code). This dataset will not have the code that identifies you. We may share this dataset with any researcher who has a use for it.

If you agree, we will also make a dataset that only has the non-identifiable sensor data from the devices. This dataset will have no identifiable information and no codes that could link back to you. This dataset can help the wider research community, and we would share it with anyone who could find it useful. This is completely optional. You can agree to take part in the study but not include your data in this open data project.

How long we will keep your data: We expect to complete this study after 3 years. After the study is over, we will we will make a copy of the data that will be stripped of all information that could identify you (including raw location data/GPS, your video, and your code). We will save this copy of your research data as long as we think it is still useful. We expect that the data will be useful for 10 years after the study is over, but we may keep it much longer.

Canceling your permission: If you change your mind later and you don’t want your research data shared with other researchers, you can cancel your permission. To cancel your permission, you have to write a letter to Santosh Kumar. When you write us a letter and cancel your permission, we will delete your information from the database. No new researchers will be able to get a copy of the data. We will not be able to take back the research data from researchers who already have the data.

After we finish this study, we will also make a copy of the data that will be stripped of all information that could identify you (including raw location data/GPS and your code). This dataset will not have the code that identifies you. If you decide to cancel your permission to share your data with other researchers after we finish this study, we will not be able to find or delete your individual research data from this copy of the dataset.

Open data set opt-in section:

If you agree, we will also make a dataset that only has sensor data from the devices that cannot identify you as an individual. This dataset will have no identifiable information and no codes that could link back to you. This dataset can help the wider mobile health (mHealth) community to learn how mobile sensor data can improve health. We would post this dataset on a publicly accessible website for anyone to download. This is completely optional. You can agree to take part in the study but not include your data in this open data project. By signing next to “Yes,” you agree that we can keep and share the de-identified sensor signals that we collect from you on a publicly accessible website.

Will you allow us to share the sensor data we collect for this study on a publicly accessible website?

YES ________________________
Signature of Participant

NO _________________________
Signature of Participant

Name of [authorized] person obtaining informed consent & Date

__________________________________________________________