La División de Poderes como fundamento para la existencia de la potestad reglamentaria del Poder Ejecutivo

The previously presented devices not just offer differing sensors and sensing technologies (i.e.,

PPGvs. ECGheart rate) but they also offer differing granularities and access means. These are

discussed below per each device. The focus lies on obtaining data in a research-usable way, i.e., numeric vales. This access is named ’pro’ access for researchers in the following sections. Since three devices (Apple Watch,Microsoft Band, andPolar H7) are consumer devices, the normal data

access means meant for consumer ’users’ are briefly presented, too.

An overview of the devices’ sensors, sampling rates and measurement units can be found in Table4.2.

4.2.2.1.

Apple Watch

While the Apple Watch offers optical heart rate, movement and location

sensing, the means to access the sensor data differs. Computed health features, such as resting heart rate, floors climbed, or exercise minutes are stored in the Health app on the iPhone. It is accessible throughHealthKitor through the Health app in form of visualisations.

Data in the Health app is backed up and synchronised across the iOS devices through the iCloud online storage (Apple Inc.,2019b), but it is not accessible directly from this cloud storage. Raw

Chapter 4. Accessing Data from Wearable Devices

Sampling Rate Unit

Nexus

heart rate 32 Hz bpm

ECG 256 Hz micro volts

EDA- skin conductance 32 Hz micro siemens

skin temperature 32 Hz ◦

C

Apple Watch

heart rate not specified bpm raw acceleration (x,y,z) 100 Hz G†

attitude (x, y, z), 100 Hz G rotation (yawn, pitch, roll), 100 Hz radians

gravity (x, y, z), 100 Hz G linear acceleration (x, y, z), 100 Hz G

magnetic field (x,y,z) 100 Hz micro tesla

Microsoft Band

Heart Rate 1 Hz bpm

RR Intervals value changed seconds EDA - Skin Resistance 0.2/5 Hz koms

Skin Temperature 1 Hz ◦C

acceleration (x,y,z) 62 Hz G

angular velocity (x,y,z) 62 Hz ◦/s

Polar Heart Rate 1Hz bpm

RR Intervals value changed 1/1024 seconds

†_{gravitational force G (9.81ms−2}

on the earth)

Table 4.2.:Overview of the sensor sampling rate and units of the devices used for the lab study. The information has been retrieved from the manufacturers’ manuals and documentation (Microsoft,2016;Polar,2018;MindMedia,2017;Apple Inc.,2018).

The potential of emerging wearable physiological sensing in the space of human-subject studies Chapter 4. Accessing Data from Wearable Devices

motion sensing data from theApple Watchis just accessible through the CoreMotionApplication Programming Interface (API)on the watch (Apple Inc.,2018). A schematic depicting the access

means are depicted in Figure4.4.

HealthKit Access. HealthKitis anAPIprovided with the iOSSoftware Development Kit (SDK)

to read and write health data to the Health database on the iPhone (Apple Inc.,2019b). This database contains health metrics of the iPhone owner, such as vital markers, fitness activities, or nutrition. Any iOS app can read and write to this database after the user’s permission is granted. Higher level features derived from the theApple Watch’s sensing data (e.g., step count

derived from the motion sensor, or heart rate fromPPGsensor) are stored in this database. This

data can be accessed programmatically (from within an app) through Apple’sHealthKit API

either on the phone or on the watch; provided that user’s permission has been granted for the specific app. No specialSDKsor libraries are needed since theHealthKit APIis integrated in

Apple’s standardSDK. Additionally to real-time data,HealthKitalso allows access to historic

health data.

In summary, access to the health related data and higher level features (including heart rate) in most cases needs to be performed either programmatically or with actual access to the device. For remote studies and data collection, an app needs to be built which incorporates the data collection mechanisms.

Raw Motion Sensor Access. The raw motion sensors, namely accelerometer, gyroscope, and magnetometer can be accessed via Apple’s standardSDK. Apple’s Core MotionAPIprovides

functions to access motion sensor data in the form of raw acceleration data and aggregated device motion features (Table4.2). Access to this data is real-time and no historic data can be accessed. While these functions allow the access of the sensor data on the watch itself, there are no readily available means to transmit this data to the phone.3

UI Data. TheApple Watchsmartwatch is the only device of the four test devices to offer a

sophisticated programmableUI. ProgrammableUIscan become data sources in themselves,

e.g., by collecting questionnaire data or user feedback. TheApple Watch’sUIhas been used to

collect experience samples during a study presented in Section5.1.

Chapter 4. Accessing Data from Wearable Devices iPhone Apple Watch Health app CoreMotion API Motion Sensor Heart Rate Sensor Computed Features HealthKit API Raw Features HealthKit API Pro B lu e too th Pro User

Third Party Apps Viz Insights Viz iCloud (Backup & sync) W iFi / G S M

Figure 4.4.:Schematic figure of data access onApple Watch. Data can be accessed programatically

by professional users using the providedAPIson the watch or phone. computed

health features (e.g., steps, burned calories, heart rate) are stored in the Health app on the phone and can be accessed via theHealthKit API. Raw motion sensing features

can just be obtained from the watch itself using a programatic approach.

4.2.2.2. Microsoft Band 2

The sensing data from the Microsoft Band can be obtained through

different means. Sensing data from the device is generally transferred to the paired phone viaBLE. There, it is stored in the Microsoft Health companion app on the

connected phone. Computed features, e.g., steps, heart rate, burned calories, can be accessed by the user in form of summaries and visualisations. Additionally, this computed data is transferred to the Microsoft Online Health service where the data is stored in the cloud. Users can access summaries and visualisations via a web dashboard. OnlineAPIsare provided to

allow developers access to this higher-level data; this function could be leveraged by researchers. This approach is not unique to theMicrosoft Band. It is the common approach to transfer data

from modern wearable fitness trackers to a proprietary mobile phone app via Bluetooth. Often, this mobile phone acts as a gateway to transfer data to a cloud service for storage from where it can accessed via a web dashboard or anAPI. In line withInternet of Things (IoT)principles, this

data can be accessible to third-party services via this offered onlineAPI.

This approach is followed for fitness wearables from, e.g., Fitbit,4_Garmin,5_{or Xiaomi.}6

4_{https://www.fitbit.com(accessed: 10/05/2019)}

5_{https://buy.garmin.com/en-GB/GB/wearables/wearables/c10001-c10002-p1.html(accessed: 10/05/2019)} 6_{https://www.mi.com/global/(accessed: 10/05/2019)}

The potential of emerging wearable physiological sensing in the space of human-subject studies Chapter 4. Accessing Data from Wearable Devices

Microsoft Health Cloud Service iOS / Android / Windows Phone Microsoft Band SDK Microsoft Health App User Pro Cloud Database User Pro API Viz Raw Features Computed Features Computed Features Computed Features B lu e too th W iFi / G S M API Viz Microsoft Band

Figure 4.5.:Schematic figure of data access on theMicrosoft Band 2. User access to higher-level

health features in form of visualisations and summaries is provided through the Microsoft Health app on the paired mobile phone or a web dashboard through the Microsoft Health Cloud service. The cloud service also offers an onlineAPI for

accessing/downloading the data. Professional access to raw sensing features can be obtained on the mobile phone viaSDK.

Additionally, theMicrosoft Bandoffers data access via a providedSDK.7ThisSDKwas provided

byMicrosoft(2016) for iOS, Android and Windows Phone, and it can be integrated in mobile phoneappsfor these platforms. ThisSDKallows direct, programatically access to real-time, raw

sensing features (Table4.2) which can be leveraged by pro users, e.g., researchers. It does not allow the access to historic sensing data. The provision of a mobileSDKfor sensing data access

is not common amongst wearable device manufacturers and is a speciality of theMicrosoft Band.

4.2.2.3. Polar H7

ThePolar H7is a representative device forBLE-enabled heart rate sensing straps.

As such, it can be paired and connected to a multitude ofBLE-enabled devices, e.g.,

mobile phones, modern computers, smartwatches, etc. It’s connectivity is based on theGATT

Heart Rate Service standard (Bluetooth Special Interest Group,2011). While the manufacturer does not offer anSDK, a developer documentation with sample source code exists (Polar,2018).

To access sensing data from thePolar H7the paired device’sBLEprogramming layerAPIhas to

be used to allow access to real-time sensing data from thePolar H7. This offers pro users the

opportunity to connect thePolar H7to a range of devices and integrate it in various research

Chapter 4. Accessing Data from Wearable Devices BLE-enabled device Polar H7 User Pro Device’s Bluetooth Programming Layer API B lu et oo th (G A T T H ea rt R at e Ser vice)

Third Party Apps

Figure 4.6.:Schematic figure of data access on the Polar H7. Access to the sensing data can

be obtained through the paired device’sBluetooth Low Energy (BLE)programming

interface or third-party apps.

applications. The access through the device’s bluetooth layer is also used by third-party apps which connect to thePolar H7, e.g., Strava8fitness app or HRVLogger byAltini(2013). These

are often meant for users of the device, e.g., for sophisticated fitness tracking, but can also be leveraged by researches, providing they allow suitable export options. E.g., HVRLogger which allows the download of the raw sensing data and additionally computedHeart Rate Variability (HRV)features. A schematic figure of data access from thePolar H7is depicted in Figure4.6.

Other examples of Bluetooth-enabled devices relying on theGATTHeart Rate service standard

exist. These devices offer the same access means. OtherECGheart rate straps are, e.g., the

successor Polar H10,9or Whaoo TICKR range.10 SomePPG-based, optical heart rate monitors

also support this standard, too, e.g., Mio AlPha.11

4.2.2.4. Nexus 10

TheNexus 10 MK2is a laboratory device with professional application and its

main purpose is provide medical sensing data in a professional/research-usable form. It offers two means: internal recording on an SD card and real-time streaming to a Bluetooth-connected Windows PC. In both cases, the device has to be firstly configured through the proprietaryBioTrace+software byMindMedia(2017). The configuration includes the type of

sensors plugged into theNexus, as well as, sampling rates of the sensors. The software also

8_{https://www.strava.com/(accessed: 08/05/2019)}

9_{https://www.polar.com/uk-en/products/accessories//h10_heart_rate_sensor(accessed: 10/05/2019)} 10_{https://uk.wahoofitness.com/devices/heart-rate-monitors(accessed: 10/05/2019)}

The potential of emerging wearable physiological sensing in the space of human-subject studies Chapter 4. Accessing Data from Wearable Devices

Windows PC Nexus 10-MK2 Mind Media (manufacturer) BioTrace+ Viz Export Pro B lu e too th S D C a rd

Figure 4.7.:Schematic of data access on theNexus. Data visualisation and export are available

through theMindMedia(2017)BioTrace+software for either streamed data (Bluetooth)

or data stored on the device-internal SD card.

needs to be used in both cases — internal recording or streaming — to access the data; the data on the SD card is stored in a proprietary format and cannot be read out-of-the-box. TheBioTrace+

software offers visualisation of the data either from the real-time streaming or from an SD card recording. In both cases, the data can be exported in various formats, e.g.,Comma Separated Values (CSV)format. An advantage of this technique is, that data can be seen in real-time to a)

allow manual inspection on the face validity of the data, and b) support applications where real-time access is necessary, e.g., biofeeback. The recording on the internal SD card can be advantageous to have a back-up of the data (in case of real-time recording on the PC) or can be used during ambulant settings where a connection to the PC is not possible. A similar approach of real-time streaming to a proprietary application and additional internal recording on an SD card, has also been applied in Shimmer devices12and theEmpatica E4 wristband. Shimmer and

Empatica are both companies providing professional sensing tools for research application.

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