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Mobile phone–based sensing software is a class of software for mobile phones that uses the phone's sensors to acquire data about the user. Some applications of this software include mental health and overall wellness monitoring. This class of software is important because it has the potential of providing a practical and low-cost approach to deliver psychological interventions for the prevention of mental health disorders,[1] as well as bringing such interventions to populations that have no access to traditional health care.[2] A number of terms are used for this approach, including "personal sensing", "digital phenotyping", and "context sensing". The term "personal sensing" is used in this article, as it conveys in simple language the aim of sensing personal behaviors, states, and conditions.

General information

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This article presents a comparison of mobile phone software that can acquire users' sensor data (in a passive manner without users' explicit intervention) and administer questionnaires (or micro-surveys triggered by sensor events). The software described below helps quantify behaviors known to be related to mental health and wellness. The list below includes both commercial and free software. To be included in this list, a software product must be able to acquire data from at least one phone sensor, and provide a minimum level of security for storage and transmission of acquired data. This list excludes software that focuses solely on collecting participant data from surveys and questionnaires.

Software table

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The following table contains general information about each mobile-based sensing software, such as who the developers are, when it was last updated, whether it is open or closed source, and the programming language and database they are based on.

Name Creator Latest release Latest release date Software license[3] Open source Programming language Data backend
AWARE[4] Web dashboard and Android client: Denzil Ferreira (Community Instrumentation & Awareness, University of Oulu); Mac OSX and iOS clients: Yuuki Nishiyama (Tokuda Laboratory, SFC, Keio University) 4.0.836 (Android); 1.14.12 (iOS) 2023 (Android and iOS) Apache License 2.0 Yes Web dashboard: PHP, HTML, JavaScript; Android client: Java & Kotlin; Mac OSX and iOS clients: Objective-C & Swift MySQL
Beiwe Research Platform[5] HSPH Onnela Lab[6] 2.0.4 (iOS)[7]

3.1.4 (Android)[8]

Aug 31, 2021 iOS

July 22, 2021 Android

BSD Licenses Yes Web dashboard: HTML, JavaScript; back-end and data analysis pipeline: Python, R, JavaScript; Android client: Java; iOS client: Swift, Objective-C Amazon Web Services
CenceMe[9] Smartphone Sensing Group,[10] Dartmouth College 1.2.0 (iOS) July 27, 2009 (iOS) Un­known No Python, Perl, PHP, Bash MySQL[9]
Context Sensing SDK Intel v1.0-beta2 (Windows Mobile); v1.8 (Android) March 18, 2016 (Android) Intel EULA Intel Discontinued this product Android: Java; Windows Mobile: C# Flexible
EARS[11] Ksana Health Android 2.038; iOS 2.1.5 August 2023 Apache License 2.0 Partial Android: Java; iOS: Swift Amazon Web Services
Empath[12] Department of Computer Science, University of Virginia Un­known 2011 Un­known No Un­known MySQL
Expimetrics[13] Louis Tay, Purdue University Un­known Un­known Proprietary No Un­known Un­known
Emotion Sense[14] Department of Psychology, University of Cambridge Beta April 25, 2017 BSD Licenses Yes Java SQLite[15]
Funf Open Sensing Framework[16] Originally at MIT Media Lab, now maintained by Behavio (Google) v0.5.0RC1 September 4, 2015 LGPL Yes Java SQLite[17]
m-Path Sense m-Path (KU Leuven) 2.8.0 (iOS and Android) July 4 2023 proprietary No App: Flutter (Dart), Dashboard: PHP, JavaScript MySQL
mindLAMP Platform[18][19] Division of Digital Psychiatry @ Beth Israel Deaconess Medical Center v2.0 August 27, 2020 BSD-3 Yes TypeScript, Python, R, Swift, Kotlin Flexible (noSQL)
mEMA Illumivu Inc Un­known Un­known Proprietary No Un­known Un­known
Metricwire Metricwire Inc Un­known Un­known Proprietary No Un­known Un­known
Mobile Sensing Platform[20] Cogito Corporation Un­known Un­known Proprietary No Un­known Un­known
movisensXS Movisens GmbH 1.1.1 January 5, 2017 Apache License 2.0 Partial Java, Kotlin[21] Un­known
Murmuras[22] University of Bonn spin-off Murmuras (based on the Menthal project) 2.2.1 August 24, 2020 Proprietary No Android: Java, Kotlin;[21] Web: Python, R, JavaScript PostgreSQL[23]
Passive Data Kit Audacious Software Coming soon Summer 2017[24] Apache License 2.0 Yes iOS: Objective-C, Android: Java, Web: JavaScript/Python/HTML SQLite
Psychlog[25] Instituto Auxologico Italiano and National Research Council of Italy Beta April 11, 2013 License-free software Yes C# MySQL
Psyt Research Psychological Technologies (PSYT Ltd) 2.1 June 2017 Proprietary No Native iOS (Objective-C), native Android (Java), JavaScript Hosted (backed by PostgreSQL)
Purple Robot[26] CBITS, Northwestern University 2.0.8 November 3, 2015 GPLv3 Yes Java PostgreSQL[23]
Radar-CNS King's College and Janssen Pharmaceutica NV 2.0.3-beta (dashboard); 0.1-alpha.2 (Android) June 23, 2017 (dashboard); April 13, 2017 (Android) Apache License 2.0 Yes Android: Java, Web: Typescript MongoDB
RealLife exp LifeData LLC Un­known Un­known Proprietary No Un­known Un­known
ResearchKit[27][28] Apple 1.5 June 7, 2017 BSD Yes Objective-C, Swift Flexible, can use Sage Bridge [29] to build own backend
Research Stack Cornell Tech's Small Data Lab and open mHealth 1.1.1 November 18, 2016 Apache License 2.0 Yes Java SQLite, but can also use Sage Bridge [29] to build own backend
SensingKit[30][31] Queen Mary University of London 0.5.1 (iOS), 0.2.0 (Android) September 20, 2018 (iOS) July 29, 2015 (Android) LGPL Yes Objective-C, Swift, Java Depends on implementation
Socialise[32] Black Dog Institute v0.2 June 16, 2017 Proprietary No iOS: Objective-C, Android: Java Un­known
unforgettable.me Unforgettable Research Services 0.9.6 (Android) December 5, 2017 Proprietary No Java, Python, JavaScript Amazon Web Services

Target audience

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The following table shows the target audience for each piece of software included in this article. Software packages that target developers assume a high level of skill in creating code and/or modifying third-party source code. Software packages that target researchers have at least one component that can be used in scientific studies with human subjects. Software packages that target individuals allow at least one component to be downloaded and installed by an end-user with no programming skills. Please note that some packages target more than one type of user.

Target audience
Name Developers Researchers Individuals
AWARE Yes Yes Yes
Beiwe Research Platform Yes Yes Yes
Cenceme No No Yes
Context sensing SDK Yes No No
EARS No Yes Yes
Empath No Yes No
Expimetrics No Yes No
Emotion Sense Yes Yes No
Funf Yes Yes Yes
m-Path Sense Yes Yes Yes
mindLAMP Platform Yes Yes Yes
mEMA No Yes No
Metricwire No Yes No
Mobile Sensing Platform No Yes No
MovisensXS Yes Yes Yes
Murmuras Yes Yes Yes
Passive Data Kit Yes Yes Yes
Psychlog Yes Yes Yes
Psyt No Yes No
Purple Robot Yes Yes Yes
Radar-CNS No Yes No
RealLife Exp No Yes No
ResearchKit Yes Yes Yes
Research Stack Yes Yes Yes
SensingKit Yes Yes Yes
Socialise Yes Yes Yes
unforgettable.me Yes Yes Yes

Mobile OS support

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The following table shows the type of mobile phone on which each software package can be deployed.

Supported OS
Name Android iOS Windows mobile Nokia
AWARE Yes Yes No No
Beiwe Research Platform Yes Yes No No
Cenceme No Yes No Yes
Context sensing Yes No Yes No
EARS Yes Yes No No
Empath No Yes No No
Expimetrics Yes Yes No No
Emotion sense Yes No No No
Funf Yes No No No
m-Path Sense Yes Yes No No
mindLAMP Platform Yes Yes No No
mEMA Yes Yes No No
Metricwire Yes Yes No No
Mobile Sensing Platform Yes No No No
MovisensXS Yes No No No
Murmuras Yes No No No
Passive Data Kit Yes Yes No No
Psychlog No No Yes No
Psyt Yes Yes No No
Purple Robot Yes No No No
Radar-CNS Yes No No No
RealLife Exp Yes Yes No No
ResearchKit No Yes No No
Research Stack Yes No No No
SensingKit Yes Yes No No
Socialise Yes Yes No No
unforgettable.me Yes No No No

Installation

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In addition to deploying mobile-based sensing software to smart phones, a control dashboard has to be either installed on a local computer or provided through the web. Some of the packages provide a web server so that one is able to have a remote dashboard. The table below shows the server platform and/or web server required for each piece of software.

Installation requirements
Name Server platform (operating system or web) Web server required
AWARE Web Aware provides both a server hosted by them or the ability to host dashboard on own server[33]
Beiwe Research Platform Web System back-end, web server, data storage on AWS
Cenceme Web Yes
Context sensing Web / Windows / Mac Depends on application
EARS Web Data storage on AWS
Empath Web Yes
Expimetrics Un­known Un­known
Emotion sense Web Depends on configuration
Funf Web Yes
m-Path Sense Web Not required. m-Path is hosted on KU Leuven servers
mindLAMP Platform Web Depends on application
mEMA Web Illumivu provides a web server for a fee
Metricwire Web Metricwire provides web server for a fee
Mobile Sensing Platform Un­known Un­known
MovisensXS Web Not required. Server hosted in ISO 27001 certified, German Data Center
Murmuras Web Not required. Own hardware servers colocated in Germany.
Psychlog Un­known Un­known
Psyt Web Not required. Server is hosted by Psyt
Purple Robot Web Yes
Radar-CNS Frontend dashboard app Yes
RealLife Exp Web LifeData provides a web server for a fee
ResearchKit Web server Yes
Research Stack Web server Yes
SensingKit Web server Depends on application
Socialise Web server Yes
unforgettable.me Web Web server on Amazon EC2, Data storage on Amazon S3, Cloudsearch

Sensor (and other) data that can be captured (part 1)

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The following table shows the types of mobile sensors from which each software package is capable of collecting sensor data. Note that the type of data collected depends on availability of the appropriate sensor hardware on a specific smartphone. Some software packages collect raw sensor data (e.g. Beiwe) whereas others collect summaries of such data (e.g. ResearchKit).

Supported sensors and data
Name Accelerometer Barometer Battery Bluetooth ECG Gravity Gyroscope Light Magnetometer Wifi
AWARE[34] Yes Yes Yes Yes No Yes Yes Yes (Android only) Yes Yes
Beiwe Research Platform[35] Yes No Yes Yes (Android only) No No Yes (iOS only) No Yes (iOS only) Yes
Cenceme[9] Yes No No Yes No No No No No Yes
Context sensing[36] Yes No Yes No No No Yes Yes, Windows mobile only No Yes
EARS[11] Yes No Yes No No No Yes Yes (Android only) No Yes
Empath[37] External sensors[12]
Expimetrics No No No No No No No No No No
Emotion sense[38] Yes No Yes Yes No No Yes Yes Yes Yes
Funf Yes No Yes Yes No Yes Yes Yes Yes Yes
m-Path Sense[39] Yes Yes Yes Yes No Yes Yes Yes Yes Yes
mindLAMP Platform Yes Yes Yes Yes No Yes Yes Yes Yes No
mEMA[40] Yes Yes No No No No No Yes No No
Metricwire Un­known
Mobile Sensing Platform[20] Yes No Yes No No No Yes No No No
MovisensXS[41] Yes No Yes Yes Yes No No Yes No Yes
Murmuras[22] not provided but possible not provided but possible not provided but possible not provided but possible No No not provided but possible not provided but possible not provided but possible not provided but possible
Passive Data Kit Yes Un­known Un­known Un­known Un­known Un­known Un­known Yes Un­known Un­known
Psychlog Yes No No No Yes No No No No No
Psyt[42][43] Yes Custom Yes Yes Custom No Custom Custom Custom No
Purple Robot[44] Yes Yes Yes Yes No Yes Yes Yes Yes Yes
Radar-CNS Yes Un­known Yes Un­known Un­known Un­known Un­known Un­known Un­known Un­known
RealLife Exp[45] No No No No No No No No No No
ResearchKit[46][28] Yes Yes not provided but possible not provided but possible No not provided but possible Yes not provided but possible Yes not provided but possible
Research Stack[47] Mobile sensor input provided through SensingKit[48] (below)
SensingKit Yes Yes, iOS only Yes Yes, Android only No Yes Yes Yes, Android only Yes No
Socialise Yes No Yes Yes No No No No No No

Sensor and data that can be captured (part 2)

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The following table shows the types of mobile sensors from which each software package is capable of collecting passive data. Note that the type of data collected depends on availability of the appropriate sensor on the smartphone.

Supported sensors and data
Name Linear accelerometer Location Audio Pressure sensor Proximity Rotation Surveys Temperature Network reachability
AWARE[34] Yes Yes Yes No Yes (Android only) Yes Yes Yes (Android only) Yes
Beiwe Research Platform[35] No Yes Yes No Yes (iOS only) No Yes No Yes
Cenceme[9] No Yes Yes No No No No No No
Context sensing[36] No Yes Yes No Yes, Windows Mobile only Yes No No Yes
EARS[11] Yes Yes Yes No No Yes Yes No Yes
Empath External sensors[12]
Expimetrics No Yes Yes No No No Yes No No
Emotion sense[38] No Yes Yes No Yes Yes Yes Yes Yes
Funf Yes Yes Yes Yes Yes Yes Yes Yes Yes
m-Path Sense[39] Yes Yes Yes No No Yes Yes No Yes
mindLAMP Platform Yes Yes No Yes Yes Yes Yes No Yes
mEMA[40] No Yes Yes No Yes Yes Yes No No
Metricwire Un­known Yes Un­known Un­known Un­known Un­known Yes Un­known Un­known
Mobile Sensing Platform[20] No Yes Yes No No No No No No
MovisensXS[41] Yes Yes Yes No No No Yes No Yes
Murmuras[22] not provided but possible Yes not provided but possible No not provided but possible not provided but possible Time and app usage triggered ESM/EMA not provided but possible not provided but possible
Passive Data Kit Un­known Un­known Un­known Un­known Un­known Un­known Un­known Un­known Un­known
Psychlog No No No No No No Yes No No
Psyt[42][43] Custom Yes Yes Yes Custom No Specialize in ESM and EMA surveys No Yes
Purple Robot[44] Yes Yes Yes Yes Yes Yes Yes Yes Yes
Radar-CNS Un­known Un­known Un­known Un­known Un­known Un­known Un­known Yes Un­known
RealLife Exp[45] No Yes No No No No Yes No No
ResearchKit[46][28] not provided but possible Yes Yes Yes not provided but possible Yes Yes not provided but possible not provided but possible
Research Stack[47] Mobile sensor input provided through SensingKit[48] (below)
SensingKit Yes Yes Yes No Yes, only on iOS Yes No No No
Socialise No Yes No No Yes No Yes No No

Support for behavioral studies

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The following table contains information regarding availability of functions, within each software package, that support behavioral experiments for scientific purposes.

Behavioral studies features
Name How does data get from phone to database? Can surveys be triggered by phone sensors? Can surveys be triggered remotely by investigator? Can sensor data config. be remotely changed? Can platform monitor data gaps and alert investigator? Does platform support running scripts on phone?
AWARE Sensor data is uploaded to an AWARE Server instance (hosted or self-hosted) when online (WiFi only or any available connection)[4] Yes[4] Yes[49] Yes[50] Un­known Un­known
Beiwe Research Platform Wifi or cellular[51] No Yes Yes Depends on implementation[52] No
Cenceme Un­known Un­known Un­known Un­known Un­known Un­known
Context sensing Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation
EARS Sensor data is uploaded to AWS when connected to Wifi or Mobile Data. Yes Yes Yes Yes Un­known
Empath Remote server connection[12] Un­known Un­known Un­known Un­known Un­known
Expimetrics Un­known Un­known Un­known Un­known Un­known Un­known
Emotion sense Wifi Yes, by using the trigger library Depends on implementation Depends on implementation Depends on implementation Depends on implementation
Funf (1) manual export or Android file transfer service, (2) manual transfer from device's memory card, (3) setting up server and configure funf to upload data to server.[17] No No Yes[53] Depends on implementation Depends on implementation
m-Path Sense Sensor data is regularly uploaded to m-Path servers when Wi-Fi is available No Yes Yes Yes No
mindLAMP Platform WiFi and Cellular Data Depends on implementation Yes Depends on implementation Depends on implementation Yes
mEMA Un­known Un­known Un­known Un­known Un­known Un­known
Metricwire Un­known Un­known Un­known Un­known Un­known Un­known
Mobile Sensing Platform Un­known Un­known Un­known Un­known Un­known Un­known
MovisensXS Cell or Wifi. Online and Offline[21] Yes[21] No[21] Yes[21] Yes[21] No[21]
Murmuras WiFi or cellular. Yes Yes Yes Depends on implementation Depends on implementation
Passive Data Kit Un­known Un­known Un­known Un­known Un­known Un­known
Psychlog Un­known No[21] No[21] No[21] No[21] No[21]
Psyt Hosted data store; automatic over-the-air background pload[43] Yes[43] In development[43] Yes[43] Yes[43] Yes[43]
Purple Robot Sensor data and user provided information is securely transmitted to custom data warehouses[44] Yes[44] Un­known Yes[44] Un­known Un­known
Radar-CNS Un­known Un­known Un­known Un­known Un­known Un­known
RealLife Exp Un­known Un­known Un­known Un­known Un­known Un­known
ResearchKit Wi-fi or cellular Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation
Research Stack Wi-fi or cellular Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation
SensingKit Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation Depends on implementation
Socialise Wi-fi or cellular No Yes No Un­known Un­known

Battery management

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The following table contains information relative to battery management for each software package. As passive data collection from smartphone sensors is a battery-intensive process, methods to maximize battery performance are important for this type of software.

Supported features
Name Relative drain on battery Methods of managing battery life
AWARE Overall battery impact on average: 19.7mA when sensing only; 24.7mA when storing locally; and 138mA when connected to server[4] Built-in location algorithm that minimizes battery drain.[54] Also uses event based sampling, opportunistic analysis and scheduled synching to reduce battery consumption[4]
Beiwe Research Platform Internal testing of Beiwe did not result in significant battery drain [5] Battery drain depends entirely on data collection settings
Cenceme Un­known Un­known
Context sensing Un­known Un­known
EARS Rates of battery drainage are affected by which sensors are activated. The EARS Android app drains around 0.38% of the battery of a Samsung Galaxy 7 every hour of collection on all sensors. On newer devices or devices with fewer sensors, a smaller percentage is drained every hour. Battery drain depends entirely on data collection settings
Empath Un­known Un­known
Expimetrics Un­known Un­known
Emotion sense Un­known To extend battery life, Emotionsense offloads computations to a remote server[55]
Funf Un­known nonspecified type of "Battery optimization"[53]
m-Path Sense Battery impact depends on selected data to collect. Location data has high impact, gyroscope is low. Battery drain can be optimized by being specific in data selection.
mindLAMP Platform Minor battery drain, approximately 0.5% per hour depending on device and collection settings. Battery drain depends entirely on data collection settings
mEMA Un­known Un­known
Metricwire Un­known Un­known
Mobile Sensing Platform Un­known Un­known
MovisensXS Continues location tracking results in 4 days of battery life[21] Special algorithms maintain a low battery usage[21]
Murmuras Testing of Murmuras did not result in significant battery drain. Battery drain depends entirely on data collection settings.
Passive Data Kit Un­known Un­known
Psychlog 5–6 hours of autonomy[21] None[21]
Psyt Varies with sensor implementation[43] No drain when backgrounded on iOS[43]
Purple Robot The battery drain (in seconds per %) of old uploader plugin was 211 seconds; after introducing a new uploader, the battery drain was 584 seconds[56] In 2014 purplerobot introduced optimizations that increased battery life 176%[56]
Radar-CNS Un­known Un­known
RealLife Exp Un­known Un­known
ResearchKit Depends on implementation Depends on implementation
Research Stack Depends on implementation Depends on implementation
SensingKit Battery performance was measured on an iPhone 5S running iOS 9.2 and the battery had the following duration performance: idle (51hrs), accelerometer (31hrs), gyroscope (28hrs), magnetometer (34hrs), device motion (21hrs), location (18hrs)[30] Un­known
Socialise Battery performance was assessed on participants' own devices. Average battery life was 21.3 hours when app was not scanning and 18.8 hours when GPS, Bluetooth and battery data was collected every 5 minutes[32] Un­known

Software maintenance and support

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The following table contains information relative to maintenance and support for each software package. The information provided in this table gives an idea of the likelihood of a package to be supported in the future.

Software maintenance and support features
Name Online documentation available User's forum / technical support How actively is software maintained? User base Support for bugs and updates Location of source code (GitHub, SourceForge, Bitbucket, Launchpad)? Funding source
AWARE Yes[33] Slack, 503 users as of Oct 29, 2019[57] Android client: actively maintained (Denzil Ferreira); iOS client: actively maintained (Yuuki Nishiyama) Used in 2722 studies across institutions worldwide. Slack and GitHub Issue tracking actively used. GitHub Academy of Finland; Tekes; EU (Marie Curie Actions)
Beiwe Research Platform Yes[52] Slack[58] 6 iOS releases, 14 Android releases[52] Beiwe is currently used in 25 studies, primarily at various Harvard Medical School teaching hospitals[6] Yes[52] GitHub NIH Director's New Innovator Award[6]
Cenceme No No Un­known Un­known Un­known Un­known Intel, Nokia, NSF, DHS
Context sensing SDK Yes[59] Intel Context sensing SDK developer's forum at Intel.com[60] Un­known Un­known From May 18, 2016, to July 3, 2017, there were two issues posted the developers forum, one of then had 2 replies from intel and the other one had one reply from intel staff[60] Intel's Context Sensing SDK's download page[61] Intel
EARS No Un­known Un­known Un­known Un­known GitHub Un­known
Emotion sense Yes[62] Developers Forum at Google Groups[63] The sensor manager for Android had 0 commits from the week of July 10, 2016 to July 3, 2017. The Android sensor data manager had 0 commits from the week of July 10, 2016 to July 3, 2017. The iOS survey manager had 0 commits from the week of July 10, 2016 to July 3, 2017. The iOS sensor manager has 0 commits from the week of July 10, 2016 to July 3, 2017. 33 topics at their Google Group's developers forum. From July 3, 2016, to July 3, 2017, there were 5 topics opened, for a total of 11 posts. The forum seems to have gone silent since March 2017. The developers forum seems to have gone silent since March 2017 and no issues have been raised in the GitHub page in the last year (July 3, 2016 to July 3, 2017). GitHub EPSRC (funding expired in 2015)
Empath No Un­known Un­known Un­known Un­known Un­known NSF
Expimetrics No Un­known Un­known Un­known Un­known Un­known Elevate Ventures[64]
Funf Yes Developer's forum at Google Groups[65] Funf open sensing framework Android library and 0 commits from week of July 10, 2016 to July 3, 2017. The processing data scripts repository had 0 commits from week of July 10, 2016 to July 3, 2017. The Funf developers google group has 338 members and a total of 229 topics, the large majority of which were started before the last year (July 3, 2016 to July 3, 2017).[65] A total of 60 issues were reported on the Funf open sensing framework at GitHub, 52 of which were resolved. No issues have been reported in the last year (July 3, 2016 to July 3, 2017). GitHub The Knight Foundation, Google
m-Path Sense Yes[66] Reddit, /r/mpath actively maintained by developers In constant development, monthly updates 38,000 App users worldwide Reddit and e-mail support Not publicly available KU Leuven
mindLAMP Platform Yes Yes Frequent updates, highly maintained. Used by hundreds of patients in studies around the world, including Harvard teaching hospitals. Yes GitHub Public
mEMA No Un­known Un­known Un­known Un­known Un­known Un­known
Metricwire No Un­known Un­known Un­known Un­known Un­known Un­known
Mobile Sensing Platform No Un­known Un­known Un­known Un­known Un­known DARPA
MovisensXS Yes[67] Technical Support Highly maintained.[67] Every Android update is prepared. ~ Quarterly Updates.[68] ~1700 Researchers. ~6000 Studies Intercom 24/7 Chat support and Email. Not available Private
Murmuras No Technical Support Frequent updates, highly maintained. Un­known Email and Phone support depending on contract. Private Commercial
Passive Data Kit Coming soon[69] No users or developers forum In the Passive data kit for Android there have been 64 commits from the week of July 10, 2016 to July 3, 2017. In the passive data kit for iOS there have been 19 commits from the week of July 10, 2016 to July 3, 2017. In the passive data kit online server there have been 75 commits from the week of July 10, 2016 to July 3, 2017 Un­known Un­known GitHub Private
Psychlog No None Not available Not available Not available SourceForge EU funding expired 2013
Psyt No Email support group >1500 commits per year Eight research projects, over 100,000 research participants Fully supported under contract (for iOS and whitelisted Android devices) Private Commercial
Purple Robot Yes No users or developers forum available There has been 0 commits from the week of July 10, 2016 to July 3, 2017. Purple robot has been forked 20 times and it has 7 contributors and 35 branches There are 44 issues open and 225 resolved. None of the reported issues has been within the last year (July 3, 2016 to July 3, 2017) GitHub Un­known
Radar-CNS No No users or developers forum available The questionnaire mobile application code had 111 commits from the week of July 10, 2016 to July 3, 2017 (4 contributors). The dashboard source code had 290 commits from the week of July 10, 2016 to July 3, 2017 (4 contributors). The functionality for Android passive plugins had 372 commits from the week of July 10, 2016 to July 3, 2017 (6 contributors). The phone sensor plugin for passive remote monitoring app had 301 commits from the week of July 10, 2016 to July 3, 2017 (6 contributors). The android app source code had 139 commits from the week of July 10, 2016 to July 3, 2017 (5 contributors). The repositories contained within Radar-CNS GitHub's account have been forked 20 times, which might be an indicator of the user/developer base Questionnaire source code has a total of 13 open issues and 13 closed issues. The dashboard source code has a total of 25 open issues and 11 issues closed. The functionality for Android passive plugins has a total of 6 issues open and 3 closed. The phone sensor plugin has 0 total issues. The android app code has 13 issues open and 14 closed. GitHub Horizon 2020 and EFPIA
RealLife Exp Yes[70] Help center[70] Not available Not available Not available Not available Private
ResearchKit Yes[71] Developers Forum at Apple Developer Forums[72] 200 commits from the week of July 10, 2016 to July 2, 2017 (96 contributors). 6 topics related to Researchkit within the developers forum, all of them opened within the last year (July 2016 to July 2017). 72 issues open and 362 closed (about a third of those issues occurred within the last year). GitHub Apple
Research Stack Yes[73][74] Developers Forum at Google Groups[47] 14 commits from the week of July 10, 2016 to July 2, 2017 (14 contributors) 32 topics in the developers forum, 11 of those topics updated within the last year (July 3, 2016 to July 2, 2017).[47] 52 issues open and 78 closed. About a third of those issues occurred within the last year (July 2016 to July 2017). GitHub Robert Wood Johnson Foundation
SensingKit Yes[48] No users or developers forum available Sensingkit for iOS source code had 282 commits from the week of July 10, 2016 to July 2, 2017 (1 contributor).Sensingkit for Android had no commits from the week of July 10, 2016 to July 2, 2017 (1 contributor). Sensingkit server platform had no commits from the week of July 10, 2016 to July 2, 2017 (1 contributor) 15 forks total in Sensingkit for Android, iOS and server There was a total of 3 issues open and 6 closed in iOS, Android and server repositories combines, all of the issues occurred within the last year (July 3, 2016 to July 2, 2017). GitHub UK Defence Science and Technology Laboratory
Socialise No No Un­known Un­known Un­known Private National Health and Medical Research Council

Security and privacy

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The following table contains information relative to encryption and secure transfer of data collected from smartphone sensors. This information is very important for a data collection app due to privacy concerns over the handling of phone data.

Security and privacy
Name Database encryption? Secure data transfer?
AWARE Locally protected by application signature and permission; enabled remotely by MySQL server deployment[75] SHA-256 with a 2048-bit long RSA strong encryption key or encrypted with any SSL certificate[33]
Beiwe Research Platform All data on phones, on the server, and in-transit use industry-standard encryption techniques. Data on phones and server are encrypted using 2048 bit RSA encryption and AES[35] SSL Encrypted connection[35]
Cenceme Un­known Un­known
Context sensing Not provided but can be accomplished using other APIs Not provided but can be accomplished using other APIs
EARS AES public-private key pairing on device + AWS encryption TLS (1.2 or greater) Encrypted connection
Empath Un­known Un­known
Expimetrics Un­known Un­known
Emotion sense Encryption is used but was unable to obtain more details Encryption is used but was unable to obtain more details
Funf RSA Depends on type of transfer but data is encoded using RSA[17]
m-Path Sense KU Leuven standard data protection protocols are followed/> TLS
mindLAMP Platform AES public-private key pairing on device + AWS encryption TLS (1.2 or greater) Encrypted connection
mEMA Un­known Un­known
Metricwire Un­known Un­known
Mobile Sensing Platform AES, public-private key pairing[76] SSL encrypted connection[76]
MovisensXS AES, public-private key pairing[21] SSL encrypted connection[21]
Murmuras Locally protected by application signature and permission. TLS/SSL with Certificate pinning[77]
Passive Data Kit Un­known SSL
Psychlog Un­known Un­known
Psyt On device (varies by platform) and back-end (Amazon Web Services RDS Postgres encrypted database[43]) Qualys A+ rated TLS[43]
Purple Robot Un­known SSL
Radar-CNS Encryption not provided yet[21] Encryption not provided yet[21]
RealLife Exp AES 256 bit encryption[70] Web app to server transmission: synchronous and asynchroonus SSL encryption; mobile app to server transmission: encoded using Base64 and encrypted using AES 256 bit encryption prior to transmission[70]
ResearchKit Not provided, thus it is the responsibility of the developer Encrypted communication between app and server not provided
Research Stack AES Can use Sage Bridge[29]
SensingKit Not provided, thus it is the responsibility of the developer Not provided, thus it is the responsibility of the developer
Socialise Un­known Un­known

Cost

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The following table contains information relative to whether a software package is free or non-free.

Cost of each platform and dependencies
Name Cost
AWARE Free
Beiwe Research Platform Free
Cenceme Un­known
Context sensing SDK Free
EARS Non-free
Empath Un­known
Expimetrics Non-free
Emotion sense Free
Funf Free
m-Path Sense Non-free
mindLAMP Platform Free
mEMA Non-free
Metricwire By quote
Mobile Sensing Platform Un­known
MovisensXS Free for students
Murmuras Free for students
Passive Data Kit Free
Psychlog Free
Psyt Non-free
Purple Robot Free
Radar-CNS Free
RealLife Exp Non-free
ResearchKit Free
Research Stack Free
SensingKit Free
Socialise Un­known

See also

[edit]

Notes and references

[edit]
  1. ^ Prevention of Mental Health Disorders Using Internet- and Mobile-Based Interventions: A Narrative Review and Recommendations for Future Research. Ebert DD, Cuijpers P, Muñoz RF and Baumeister H (2017) Front. Psychiatry 8:116. DOI: 10.3389/fpsyt.2017.00116
  2. ^ Behavioral intervention technologies: evidence review and recommendations for future research in mental health. Mohr DC, Burns MN, Schueller SM, Clarke G, Klinkman M. General Hospital Psychiatry Volume 35, Issue 4, July–August 2013, Pages 332-338. DOI: 10.1016/j.genhosppsych.2013.03.008
  3. ^ License(s) stated are only a summary. Some software packages may use libraries under different licenses.
  4. ^ a b c d e AWARE: mobile context instrumentation framework; Ferreira D, Kostakos V and Dey AK Front. ICT (2015); 2:6; DOI:10.3389/fict.2015.00006
  5. ^ a b New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research; Torous J, Kiang MV, Lorme J, Onnela JP; JMIR Ment Health (2016);3(2):e16 DOI:10.2196/mental.5165
  6. ^ a b c Onnela lab's website. Retrieved June 23, 2017
  7. ^ "Beiwe2". App Store. Retrieved 2021-12-03.
  8. ^ "Beiwe2 - Apps on Google Play". play.google.com. Retrieved 2021-12-03.
  9. ^ a b c d CenceMe – Injecting Sensing Presence into Social Networking Applications; Miluzzo E., Lane N.D., Eisenman S.B., Campbell A.T. (2007); In: Kortuem G., Finney J., Lea R., Sundramoorthy V. (eds) Smart Sensing and Context. EuroSSC 2007; Lecture Notes in Computer Science, vol 4793. Springer, Berlin, Heidelberg DOI: 10.1007/978-3-540-75696-5_1.
  10. ^ Smartphone Sensing Group at Darmouth's website. Retrieved June 30, 2017.
  11. ^ a b c d Lind, M. N., Byrne, M. L., Wicks, G., Smidt, A. M., & Allen, N. B. (2018). The Effortless Assessment of Risk States (EARS) Tool: An Interpersonal Approach to Mobile Sensing. JMIR Mental Health, 5(3), e10334–10. [1]
  12. ^ a b c d Empath: a continuous remote emotional health monitoring system for depressive illness; Robert F. Dickerson, Eugenia I. Gorlin, John A. Stankovic; WH '11 Proceedings of the 2nd Conference on Wireless Health; Article No. 5; San Diego, California — October 10–13, 2011; DOI: 10.1145/2077546.2077552
  13. ^ "Purdue related startup creates experience capturing platform that could replace, improve traditional survey tools", Purdue Newsletter 4th quarter (2016). Retrieved June 25, 2017
  14. ^ Happier People Live More Active Lives: Using Smartphones to Link Happiness and Physical Activity; Neal Lathia, Gillian M. Sandstrom, Cecilia Mascolo, Peter J. Rentfrow; (2017); PLoS ONE 12(1): e0160589; DOI: 10.1371/journal.pone.0160589
  15. ^ emotionsense.github.io/data.html. Retrieved July 4, 2017.
  16. ^ Social fMRI: Investigating and shaping social mechanisms in the real world; Nadav Aharony, Wei Pan, Cory Ip, Inas Khayal, Alex Pentland; Pervasive and Mobile Computing (2011); DOI:10.1016/j.pmcj.2011.09.004
  17. ^ a b c funf.org/journal.html. Retrieved July 4, 2017.
  18. ^ "mindLAMP Platform".
  19. ^ Torous, John; Wisniewski, Hannah; Bird, Bruce; Carpenter, Elizabeth; David, Gary; Elejalde, Eduardo; Fulford, Dan; Guimond, Synthia; Hays, Ryan; Henson, Philip; Hoffman, Liza (2019-06-01). "Creating a Digital Health Smartphone App and Digital Phenotyping Platform for Mental Health and Diverse Healthcare Needs: an Interdisciplinary and Collaborative Approach". Journal of Technology in Behavioral Science. 4 (2): 73–85. doi:10.1007/s41347-019-00095-w. ISSN 2366-5963. S2CID 150589575.
  20. ^ a b c Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders; Place S, Blanch-Hartigan D, Rubin C, Gorrostieta C, Mead C, Kane J, Marx BP, Feast J, Deckersbach T, Pentland A, Nierenberg A, Azarbayejani A; J Med Internet Res (2017);19(3):e75 DOI:10.2196/jmir.6678
  21. ^ a b c d e f g h i j k l m n o p q r s t u Personal communication.[full citation needed]
  22. ^ a b c "Murmuras website".
  23. ^ a b tech.cbits.northwestern.edu/2013/10/04/purple-robot-importer-purple-robot-warehouse. Retrieved June 30, 2017.
  24. ^ PassiveDataKit website. Retrieved June 25, 2017
  25. ^ An open source mobile platform for psychophysiological self tracking; Gaggioli A, Cipresso P, Serino S, Pioggia G, Tartarisco G, Baldus G, Corda D, Riva G; Stud Health Technol Inform. (2012);173:136-8 DOI:10.3233/978-1-61499-022-2-136
  26. ^ Purple: A Modular System for Developing and Deploying Behavioral Intervention Technologies; Schueller SM, Begale M, Penedo FJ, Mohr DC; J Med Internet Res 2014;16(7):e181; DOI:10.2196/jmir.3376
  27. ^ ResearchKit documentation. Retrieved June 23, 2017
  28. ^ a b c Apple’s ResearchKit: smart data collection for the smartphone era?; Jennifer Jardine, Jonathan Fisher, Benjamin Carrick; Journal of the Royal Society of Medicine; Vol 108, Issue 8, pp. 294 - 296 (2015); DOI:10.1177/0141076815600673.
  29. ^ a b c developer.sagebridge.org. Retrieved July 2, 2017.
  30. ^ a b “SensingKit: Evaluating the Sensor Power Consumption in iOS devices”; Kleomenis Katevas, Hamed Haddadi and Laurissa Tokarchuk; 12th International Conference on Intelligent Environments (IE'16); September 2016; London, UK. Retrieved June 23, 2017
  31. ^ Poster: SensingKit: a multi-platform mobile sensing framework for large-scale experiments; Kleomenis Katevas, Hamed Haddadi, Laurissa Tokarchuk; Published in: Proceeding MobiCom '14 Proceedings of the 20th annual international conference on Mobile computing and networking; Pages 375-378; Maui, Hawaii, USA — September 07–11, 2014; DOI: 10.1145/2639108.2642910
  32. ^ a b c Using Mobile Phone Sensor Technology for Mental Health Research: Integrated Analysis to Identify Hidden Challenges and Potential Solutions. Boonstra TW, Nicholas J, Wong QJ, Shaw F, Townsend S, Christensen H (2018) J Med Internet Res 20(7):e10131. [2]
  33. ^ a b c Awareframework tutorials. Retrieved June 26, 2017.
  34. ^ a b awareframework.com/sensors. Retrieved July 1, 2017.
  35. ^ a b c d Beiwe research manuals provided by investigator.
  36. ^ a b Rather than giving access to specific phone sensors, context Sensing SDK provides access to "context states", each one of those states drawing data from combination of sensors. We have listed here the sensors and not the states referred to in the developers manual located at software.intel.com/en-us/documentation/context-sensing-sdk-for-android-states-datasheet for Android and at software.intel.com/en-us/documentation/context-sensing-sdk-for-windows-states-datasheet for Windows mobile. Retrieved July 1, 2017.
  37. ^ The empath platform's sensors are external to the phone.
  38. ^ a b emotionsense.github.io/sensors.html. Retrieved July 1, 2017.
  39. ^ a b [3]. Retrieved July 7, 2023.
  40. ^ a b ilumivu.com/solutions/ecological-momentary-assessment-app/in-phone-sensors. Retrieved July 1, 2017.
  41. ^ a b movisens.com/en/products/movisensxs. Retrieved July 2, 2017.
  42. ^ a b www.psyt.co.uk/research. Retrieved July 2, 2017.
  43. ^ a b c d e f g h i j k l Email communication, Katie Brown, Psychological Technologies (Psyt Ltd).
  44. ^ a b c d e tech.cbits.northwestern.edu/purple-robot. Retrieved June 27, 2017.
  45. ^ a b www.lifedatacorp.com/features-reallife-exp-mobile-app. Retrieved July 2, 2017.
  46. ^ a b ResearchKit provides data collection in two ways: (1) through predefined macros for detection of active tasks, where each task state is extracted from information obtained through a combination of phone sensors (please refer to table at researchkit.org/docs/docs/ActiveTasks/ActiveTasks.html); and (2) through the iOS HealthKit and CoreMotion (https://developer.apple.com/documentation/coremotion developer.apple.com/documentation/coremotion) APIs.
  47. ^ a b c d Researchstack developers forum at Google groups. Retrieved July 2, 2017.
  48. ^ a b c sensingkit.org. Retrieved July 2, 2017.
  49. ^ awareframework.com/context. Retrieved July 4, 2017.
  50. ^ awareframework.com/run-a-study-with-aware. Retrieved July 4, 2017.
  51. ^ "Beiwe Wiki". wiki.beiwe.org. Retrieved 2018-01-19.
  52. ^ a b c d e "Beiwe Wiki". wiki.beiwe.org. Retrieved January 19, 2018.
  53. ^ a b funf.org/about.html. Retrieved July 4, 2017.
  54. ^ www.awareframework.com/locations. Retrieved July 4, 2017.
  55. ^ Speakersense: Energy efficient unobtrusive speaker identification on Mobile Phones; in Pervasive computing: 9th International Conference, Pervasive (2011) San Francisco; Edited by K Lyons, J Hightower, EM Huang
  56. ^ a b Purplerobot blog entry about battery management. Retrieved July 4, 2017.
  57. ^ awareframework.slack.com. Retrieved June 24, 2017
  58. ^ a b onnelalab.slack.com https://onnelalab.slack.com/. Retrieved January 19, 2018. {{cite web}}: Missing or empty |title= (help)[title missing]
  59. ^ Context Sensing SDK online documentation. Retrieved June 29, 2017.
  60. ^ a b Context sensing SDK Developers Forum. Retrieved June 29, 2017.
  61. ^ Context Sensing SDK download page. Retrieved June 29, 2017.
  62. ^ emotionsense.github.io. Retrieved July 3, 2017.
  63. ^ Emotion Sense Developer's forum at Google Groups. Retrieved June 30, 2017.
  64. ^ Elevate Ventures List of Awardees 2017. Retrieved July 3, 2017.
  65. ^ a b Funf developers forum at Google groups. Retrieved June 26, 2017
  66. ^ [4]. Retrieved July 7, 2023.
  67. ^ a b MovisensXS documentation. Retrieved June 26, 2017
  68. ^ "MovisensXS Archives - movisens GmbH". 3 October 2022.
  69. ^ passivedatakit.org/docs. Retrieved July 3, 2017.
  70. ^ a b c d lifedata.zendesk.com/hc/en-us. Retrieved July 4, 2017.
  71. ^ researchkit.org. Retrieved July 3, 2017.
  72. ^ forums.developer.apple.com/community/researchkit. Retrieved July 3, 2017.
  73. ^ http://researchstack.org/documentation. Retrieved July 2, 2017.
  74. ^ Researchstack webinar on youtube. Retrieved July 2, 2017.
  75. ^ awareframework.com/encrypting-a-studys-database. Retrieved July 4, 2017.
  76. ^ a b Mobile Sensing Platform eMethods document (PDF). Retrieved July 4, 2017.
  77. ^ "Certificate and Public Key Pinning".
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