Helping older people: is there an app for that?

Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 00 (2016) 000–000 www.elsevier.com/locate/procedia 1877-0509 © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge. Conference on ENTERprise Information Systems / International Conference on Project MANagement / Conference on Health and Social Care Information Systems and Technologies, CENTERIS / ProjMAN / HCist 2016, October 5-7, 2016 Helping older people: is there an app for that? António Cunhaa * , Evandro Cunhab Emanuel Peresa, Paula Trigueirosc aUniversity of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal and INESC TEC - INESC Technology and Science (formely INESC Porto) bUniversity of Trás-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal cLAB2PT, Escola de Arquitectura, Universidade do Minho, Azurém – 4800-058 Guimarães, Portugal Abstract From social networks to health and fitness, everyday a lot of mobile devices applications (apps) are being developed. The variety and availability is such that people start to think that indeed “there's an app for everything”. Many of these apps address either problems or characteristics that affect older people and that are related with the ageing process (e.g. memory and visual aids apps). They can effectively help people and are under constant evolution. However, the lack of knowledge about these available technological aids can undermine its dissemination and consequently the help that people really receive, especially those who need it the most: older people. As such, a methodological search for available aid apps was made both in Google Play and in iTunes: 536 were selected, their classification analysed and the kind of help that they provide identified. It was noted that either in Google Play or in iTunes the apps' categories are similar. Furthermore, it is not easily perceived what the type of help that each app can provide is and how is it provided. Hence, based on the results from the aforementioned methodological search, this paper proposes a new scalable tree-based classification methodology for aid apps, which is considered more suited to perceive what the available aid apps for mobile devices are. The existing apps were then characterized based on the proposed classification, to determine what the main aid that they provide is. © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge. Keywords: Apps, Classification; Aid; Mobile devices; Older people. * Corresponding author. Tel.: +351-259-350-369. E-mail address: [email protected] 2 António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 1. Introduction Population ageing is progressing rapidly in the world, especially in developed countries. This tendency is creating an attractive market for most information and communications technology (ICT) products and applications, as well as for smartphones and other personal technological devices. Since Apple launched its trademark catchphrase “There’s an app for that”, people started to imagine that there's an app for everything. This catchphrase is even defined in the Urban Dictionary1 as a possible answer to other peoples' problems. Everyday, a great deal of apps is being developed for a variety of purposes. Many address either problems or characteristics that affect older people and may include functionalities known to be commonly related to the ageing process, such as: memory, visual and haptic aids; features to minimize error and safety features2. Some apps are specially designed to facilitate the use of smartphones by older people. As such, they may be focused on their interface, namely by simplifying its general appearance, reducing the number of features and steps for basic tasks and increasing pictures' size and the text font. Knowing that technology is constantly evolving and helping to solve new problems, the potential of the aforementioned technologies for helping older people is far superior to the help that is indeed received. The usual barriers to the use of ICT products and applications by older people are related to the devices’ accessibility and support, to age, marital status, education and health3. Particularly when regarding aid apps, another possible reason is the lack of knowledge about the available aids and their usefulness. There is also an excess of information and permanent changes of available solutions. If it is not expected that a common smartphone user searches for novelties in apps stores everyday, when it comes to an older person this simply won’t happen. Perceiving usefulness is a strong motivation for the use of ICT3. A methodological search made in Google Play and iTunes for apps considered to be of help to people is presented: 536 were selected, their classification analysed and the kind of help that they provide identified. Based on its results, this paper proposes a new scalable tree-based classification methodology for aid apps, which is considered more suited to perceive what the available aid apps for mobile devices are. Then, the existing apps are characterized based on the proposed classification, to determine what the main aid that they provide is. With the proposed classification methodology, the authors intend to contribute to better organize apps and to clarify how smartphones might effectively help older people. The rest of the paper is structured as follows: in Section 2, some related work regarding apps classification schemas is presented. Then, in Section 3, the methodology used for selecting existing apps that might be of help to older people is detailed. Google Play and iTunes apps classification and organization schemas are compared in Section 4. Finally and just before the conclusions that derived from this study, presented in Section 6, a new scalable tree-based apps classification methodology, focused on problems or characteristics that affect older people and that are related with the ageing process, are presented and discussed in Section 5. 2. Related work The classification of applications for mobile devices is made by those who develop them in the submission process to an app store. This may mislead users, especially in app stores with permissive publication policies. Additionally, each store relies on its own classification scheme, targeted to its functionality. For instance, the Amazon app store focuses on readers, hence its classification scheme is more directed to that target-audience than to common users. As such, it only hosts apps for the Kindle eBook reader4. West et al.5 in 2012 conducted a study with the objective to overview the developers’ written descriptions of health and fitness apps and to appraise each app’s potential for influencing behaviour change. They analysed the descriptions of 3336 paid apps from the health and fitness categories, available on iTunes during February 2011. Then they were categorized using the Precede-Proceed Model (PPM)6, which identifies the functions or goals of health-related mobile apps into three categories: predisposing, enabling, and reinforcing. In 2014, Wang A. et al.7 proposed a classification scheme for analysing apps used to prevent and manage disease in late life. Their purpose was to facilitate the selection of mobile applications by older adults so that they can choose the most appropriate apps for them. They selected 199 apps from the “Health & Fitness” category of iTunes, analysed António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 3 the developers' description and constructed a classification scheme for the classification of mobile applications according to three dimensions: 1. the PPM categorization of West et al.5 expanded with; 2. whether the apps are for disease management and/or prevention; 3. whether they are related to physical and/or mental health. The authors point out as limitations that they adopted a generalized classification scheme rather than a finer-grained one and therefore it provides older adults little specific information regarding particular health conditions in which they might be interested. Furthermore, they chose to consider those apps that would have potential relevance for older adults and not people of all ages. In a scenario in which a person wants to search and find an app suitable for its own needs, it would be more useful to have a unique classification scheme, according to which all apps are classified. This scheme should be independent of the store where a given app is marketed and user-defined. 3. Aid apps selection methodology To identify existing mobile applications that might be of help to older people, the authors began by determining a set of problems or characteristics that can affect them and that are related with the ageing process. Then, a systematic search was conducted in two of the most popular apps stores, to identify the apps that comply with the defined criteria. 3.1. Search keywords determination To identify existing mobile applications that might be of help to older people, a systematic search was conducted using two of the most popular mobile operating systems (OS) apps stores: Google Play (Android, Google) and iTunes (iOS, Apple). According to the International Data Corporation8, in the end of the second quarter of 2015, Android had 82.8% of the worldwide smartphone OS market share and iOS had 13.9%. The remainder OS only represent 3.3%. To begin the process that led to the aforementioned systematic search, the main human capabilities that can change with the ageing process were determined and are presented in Table 1 a). Thereafter, a set of 76 related keywords - mainly substantives such as “arm”, “nose”, “memory”, “taste” and “cholesterol”- was chosen. The full keyword list is presented in Table 1 b). 3.2. Apps selection The process continues by entering each of the related keywords - Table 1 b) - on both the preceding apps stores' search engines. Mobile applications were selected in two stages: 1. Pre-selection - A first set of apps was selected based solely on each mobile application name, title or image. Any one of these characteristics should suggest that it was an aid to an older person. Those apps that seemed similar or duplicated were ignored after the tenth occurrence. The list of results was analysed until either the results were no longer related with this paper's purpose or after reaching the 100th mobile application. 2. List validation - Each app that resulted from the pre-selection stage was then analysed and reselected if, by reading its description, it was confirmed that it might of help to older people. Otherwise, it was rejected. For the final list of apps, both their store Link and Category were registered. After finishing the systematic search, a total of 536 apps were considered to be of some kind of help to an older person. As a remark, the mobile applications were selected based only on the description available on the app stores. None of them was tested. The authors are aware of some risks, negative issues and worrying deficiencies in existing apps, but these matters are not in this paper's scope. 4 António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 Table 1. Main capabilities’ changes during people aging and Result keywords a) Main capabilities’ changes during people aging Capabilities changes Consequences Sensory impairments Vision impairment: blurred vision; central image distortion; blurred vision; sensitive to brightness; loss of visual field; poor night vision. Hearing impairment: Problems listening to the phone; difficulty following conversations; perception that others murmur Taste and smell impairment: Loss of appetite, weight loss, malnutrition (weakened immunity) Touch impairment: Increased thermal pain threshold Motor impairment Overall decrease of energy and vigour; joint degeneration; postural instability; Cognitive impairments Loss of memory, concentration and organization Body changes Urinary problems; cardiac and respiratory problems; weakened immunity; loss of blood flow Appearance change Appearance of wrinkles and blemishes; Loss of skin elasticity; Hair colour loss; Loss of muscle mass b) Result keywords ankles, back, blood pressure, breath, capability, care, cognitive, cholesterol, deaf, dementia, difficulty, disability, distraction, ear, elder, esteem, evaluation, eyes, eyesight, fat, feel, finger, flavour, foot, great, hand, head, health, hear, hearing, heart rhythm, heavy, helper, humour, illusion, injury, kitchen, knees, leg, listen, look, looking, me, memory, mental, motor, mouth, neck, nose, ocular, odour, old people, physical, physiotherapy, psychological, psychologist, relax, savourless, senior, shoulder, sight, skinny, smell, stress, surd, tact, taste, test, tester, therapy, thin, touch, trauma, view and vision. 4. Analysis of Google Play and iTunes categories: the user’s perspective Google Play and iTunes have their apps organized by categories that once compared have multiple similarities. The 536 apps that resulted from the systematic search presented in section 3 are distributed in both stores, according to their respective categories schema. To understand how, the authors opted for:  categories that shared the same name were grouped;  similar categories that did not shared the same name were grouped in a new category whose name comprises the designations of both stores (e.g. categories such as "Utilities" from iTunes and "Tools" from Google Play were grouped in a new category named "Tools & Utilities”);  completely different categories have remained. Figure 1 presents the graphic with the 536 selected apps, organized by grouped categories, as previously explained. These categories are organized by descending order, based on the number of apps that each one contains. Also, apps that were available on both platforms are represented under the label "Both". Through the analysis of the graphic depicted in Figure 1, the most numerous category is “Health & Fitness” with 250 apps: 158 belonging to Google Play, 83 from iTunes and 10 available in both stores. The following category is “Medical”, with 102 apps. Together, these two categories - directly related to the notions of “help” - have 352 apps, which is more than half of the 536 selected apps. Considering both the aim and the keywords of the methodology used to select the aid apps, this was to be expected. The remaining apps are distributed in diverse categories. The most numerous are: “educational” with 33, “games” has 29, 27 in “communication” and “lifestyle” with (23). Together, they have 112 apps, which is the total number of apps of the remainder categories listed: “Tools & Utilities”, “Books & Reference”, “Entertainment”, “Productivity”, “Social”, “Photo & Video & Multimedia”, “Food & Drink”, “Travel & Local”, “Music & Audio”, “Sports” and “Business”. António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 5 These latter categories are not easily associated with the concept of “help” and it is not perceptible how their apps can be of help to older people. Fig. 1. Selected Apps organized by grouped categories. 5. Help Apps To characterize the help that the selected apps can provide they were re-organized in: help-type, which is a noun that characterizes the type of help; and help-how, which is a set up to three words that typify the provided help. Table 2 presents a list of “help-type” categories with at least four attributed apps. Table 2. Considering the previously selected apps, this table reorganizes them and presents a list of “help-type” categories, with at least four attributed apps. Diagnostic 64 Magnifier 6 Physical activity 5 Speed 10 Visual 21 Drugs recognition 5 Step counter 5 Strengthen 10 Hearing 14 Pictogram-to-speech 5 Auto-localization 4 Calculation 9 Memory 4 Body mass index estimation 4 Protection 16 Injury rehabilitation 8 History 49 Communicate 4 Drugs reminder 8 Injury prevention 7 Blood pressure 20 Reassurement 4 Eyes - Blue light 6 Posture correction 7 Weight 6 Informative 69 Simulation 6 Visual stimulation 7 Calories consumption 5 Good health 12 Slimmer appearance 6 Cognitive abilities 5 Organize activities of daily living 4 SOS Informative 10 Trainer 221 Recognition 5 Improve 152 Dementia 7 Memory 34 Tutorial 49 Relaxation 38 Cholesterol control 5 Relaxation 25 Injury rehabilitation 8 Speech-to-text 18 Physical care 4 Focus 15 Sign language 8 Text-to-speech 18 Wheel chair support 4 Logic 15 Improve Selfesteem 7 Amplify 15 Interface 3 Fitness 14 Massages 4 SOS Request 8 Measurement 33 Improve breathing 12 Risk estimation 7 Heart beats 10 Physiotherapy 10 6 António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 Through the analysis of the previously selected apps, ten categories were identified and are represented in Table 2 in bold and with a gray background. All of them have at least one “help-how” subcategory with more than three apps selected, except for the “Interface” category. Other categories can be added when the need arises. The next subsections will provide a definition for each of the aforementioned ten “help-type” categories, with examples of identified “helphow” and the respective selected apps. 5.1. Diagnosis This category considers applications that based on a user survey and data acquisition from sensors (both internal and external), seek to provide an indicative diagnosis. Most the times, developers advise users to confirm the indicative diagnosis with medical experts. From the selected apps, 64 fit this purpose. Twenty different “help-how” categories were identified. From these, three were more relevant having 39 in 64 apps. A few examples of apps belonging to these categories are:  “Diagnosis/Visual”: “Eye Care Plus” app10 allows for a visual acuity test, namely Snellen chart, LoGMAR table, table-Sivtsev Golovin, Landolt C and E rotary table.  “Diagnosis/Hearing”: “Hearing test” is a hearing test to check the level of speech understanding11. 5.2. History The History category has applications that use the smartphone to record the history of events. A total of 49 apps that fit this purpose were identified, along with 13 different “help-how” categories. From these, 4 were deemed more relevant, with 35 apps. Some examples are:  “History/Blood pressure”, “History/Weight”: “Bood Pressure diary” helps to keep record of blood pressure, pulse and weight readings, taken by doctors or at home. Data records include site and position, systolic and diastolic, heart rate (pulse), weight (kg / lb) and comments, which are presented either as statistical or in graphics12.  “History/Organize activities of daily living”: “CarePlan inmente”, can help to create a structured and organized life for people with dementia, while supervising daily activities13. 5.3. Improve Applications that somehow improve users' skills were considered in the Improve category, having been identified 152 apps and 24 different “help-how” categories. With 132 apps, 12 of the latter were considered more relevant. A few apps examples are presented next:  “Improve/Amplify”: The “Hear” app helps people with hearing deficit to more accurately control both the direction as the area from which they receive sound14.  “Improve/Relaxation”: “Sleep Helper” plays gentle music, creating a special atmosphere to help overcome the disadvantages factors of sleep insomnia and to improve sleep quality15.  “Improve/Text-to-speech”: “AAC Speech” is an app that provides a generic communication tool for anyone with speech disabilities. It forms grammatically correct sentences when a series of pictograms are clicked and then speaks them aloud (text-to-speech)16. 5.4. Informative This category has applications that inform users about subjects that they need help with. From the previously selected apps, 69 were placed here and 22 different “help-how” categories were identified. With a combined total of 42 apps, 6 “help-how” categories were considered more relevant. A few example apps from some of these more relevant categories are:  “Informative/Good health”: “Nutrition Facts” is a quick guide that allows to search 8000 foods for accurate nutrition and facts, including fat, cholesterol, protein, carbs, calories, omega 3 and others17. António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 7  “Informative/SOS Informative”: “In Case of Emergency” is a guide to help senior citizens and their families to prepare to a medical emergency18.  “Informative/Dementia”: “BPSD Guide” app is a guide for medical personnel and caretakers caring for persons living with dementia and that have behavioral and psychological symptoms19. 5.5. Interface Apps that use the smartphone interface to interact or to control other devices, or that allow to remotely control a smartphone, were considered to this category. A total of 3 apps were identified, along with 2 different “help-how” categories.  “Interface/Wheel chair”: “Tecla” works as an input method which enables external access to android and to most of its functions20.  “Interface/Hearing aid”: “TruLink Hearing” app connects the user hearing aids to its smartphone to easily stream the phone's sound directly to its ears21. 5.6. Measurement Applications based on sensors (internal or external) that measure and estimate magnitudes of the user's activities were considered in the “Measurement” category, having been identified 33 apps and 10 different “help-how” categories. With 24 apps, 4 of the latter were considered more relevant. A few example apps from some of these more relevant categories are:  “Measurement/Heart beats”: “Cardiio” measures the user's heart rate and relates it with its health. It also has effective workouts to get in shape and tracks the progresses made22. This app can also be classified in the “Tutorials” and “Trainer” help-type categories.  “Measurement/Step counter”: “Pacer” counts a user's steps to provide help in getting an active life23. This app can also be placed in the “Tutorial” and “Trainer” help-type categories. 5.7. Protection This category has applications to protect the user by creating actions and/or preventive alarms. A total of 16 apps that fit this purpose were identified, along with 4 different “help-how” categories. With a combined total of 14 apps, 2 “help-how” categories were considered more relevant. A few examples of apps belonging to these categories are:  “Protection/Drugs reminder”: The “Med Helper Pill Reminder” app keeps track of user prescriptions, manages medications intake and stock, as well as doctor's appointments24.  “Protection/Eyes - Blue light”: “Eyes Protector Bluelight” warns about prolonged exposure to smartphones' blue light25. 5.8. Simulation Applications that allow to foresee the impact of certain products or actions were considered in the “Simulation” category, having been identified 6 apps and 1 “help-how” category - “Slimmer appearance” - with 6 apps. Some examples are:  “Simulation/Slimmer appearance”: “Slim & Skinny” can generate a perfect figure26. 5.9. Trainer In the Trainer category, tutorial applications that teach techniques and that propose a training plan to achieve certain goals were considered. Typically, these apps also monitor the training progress by means of sensors (internal or external) and/or by the manual introduction of feedback information. With 221 apps and 35 different “help-how” 8 António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 categories identified, 16 of the latter (summing up 193 apps) were considered more relevant. A few example apps from some of these more relevant categories are:  “Trainer/Memory” and “Trainer/Focus”: “Brain-Train” is an app that selects exercises promoting creative thinking, analytical vision, improved concentration, memory, and processing speed27.  “Trainer/Relaxation”: “Calm - Meditate, Sleep, Relax” teaches how to meditate, help sleep and to relax28. It also fits in the “Tutorials” and the “Improve” help-type. 5.10. Tutorials This category has informative applications that in addition to inform, also teach users on how to apply techniques to achieve a particular purpose. A total of 49 apps were identified, along with 19 different “help-how” categories. Four categories were deemed more relevant, with 27 apps, such as:  “Tutorials/Injury rehabilitation”: “Strappt” is an app to assist on applying strapping techniques for injury rehabilitation and prevention29.  “Tutorials/Sign language”: “Sign Language” helps to learn how to fingerspell words, numbers, sign basic sentences, idioms, deaf culture30.  “Tutorials/Improve Self-steem”: “Free Hypnosis Self Esteem” helps to boost confidence through video “hypnosis session”31. Summing up, from a general analysis of Table 2, four app groups stand out: 1) The “Trainer” and “Improve” categories with 221 and 152 apps, respectively, represent 56% of the previously selected aid apps. They provide a wide range of different ways of help and are, presently, the most available aids. 2) Aids from the “Informative” (69 apps) and from the “Diagnostic” (64 apps) categories represent 20% of the considered apps. 3) Also representing 20% of the selected apps are the “Tutorial”, “History” and “Measurement” categories, with 49, 49 and 33 apps, respectively. 4) Finally, “Protection”, “Simulation” and “Interface” categories represent only 4% of the total number of selected apps, which is not relevant. This analysis was obtained based on the previously selected applications considered to be of help to people, within the defined selection criteria and to the systematic search date. It is to be expected that the available aid apps change with time. This is why the use of a classification schema like the one proposed in this paper is important, because it will allow people to realize what is available. 6. Conclusions A systematic search was conducted in two of the most popular apps stores - Google Play and iTunes - to identify apps that the authors considered to be of help to older people. The search result was the identification of 536 apps. In the aforementioned stores, apps are organized according with each store’s categories schema, which are similar when compared and do not allow to easily perceive what is the type of help that each app can provide and how is it provided. This paper proposes a new scalable tree-based classification methodology for aid apps based on two types of categories – “help-type” and “help-how” - which is considered more suited to perceive what the available aid apps are. The identified apps were then characterized based on the proposed classification and categories were selected, to determine what the main aid that they provide is. As future work, a model that allows the identification of apps based on the ageing-related changes in the human body is in its final development stage. António Cunha et al. / Procedia Computer Science 00 (2016) 000–000 9 Acknowledgements This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project «POCI01-0145-FEDER-006961», and by project Lab2PT - Landscapes, Heritage and Territory laboratory - AUR/04509 and FCT through national funds and when applicable of the FEDER co-financing, in the aim of the new partnership agreement PT2020 and COMPETE2020 - POCI -01-0145 FEDER 007528. References 1. There’s an app for that, Urban Dict. (n.d.). http://www.urbandictionary.com/define.php?term=There%27s+an+app+for+that (accessed April 17, 2015). 2. S. Kurniawan, Older people and mobile phones: A multi-method investigation, Int. J. Hum.-Comput. Stud. 66 (2008) 889-901. doi:10.1016/j.ijhcs.2008.03.002. 3. T. Heart, E. Kalderon, Older adults: are they ready to adopt health-related ICT?, Int. J. Med. Inf. 82 (2013) e209-231. doi:10.1016/j.ijmedinf.2011.03.002. 4. Giacomo Berardi, Andrea Esuli, Tiziano Fagni and Fabrizio Sebastiani. Multi-Store Metadata-Based Supervised Mobile App Classification. Proceedings of the 30th ACM Symposium on Applied Computing (SAC 2015), Salamanca, ES, pp. 585-588, 2015 5. J.H. West, P.C. Hall, C.L. Hanson, M.D. Barnes, C. Giraud-Carrier, J. Barrett, There’s an App for That: Content Analysis of Paid Health and Fitness Apps, J. Med. Internet Res. 14 (2012). doi:10.2196/jmir.1977. 6 Green, L.W., & Kreuter, M.W. Health Promotion Planning: An Educational and Environmental Approach, 2nd edition (Palo Alto: Mayfield Publishing Co., 1991). 7. A. Wang, N. An, X. Lu, H. Chen, C. Li, S. Levkoff, A Classification Scheme for Analyzing Mobile Apps Used to Prevent and Manage Disease in Late Life, JMIR Mhealth Uhealth. 2 (2014) e6. doi:10.2196/mhealth.2877. 8. International Data Corporation (IDC). (2015). Worldwide Quarterly Mobile Phone Tracker. http://www.idc.com/prodserv/smartphone-osmarket-share.jsp (accessed February 24, 2016). 9. M.N.K. Boulos, A.C. Brewer, C. Karimkhani, D.B. Buller, R.P. Dellavalle, Mobile medical and health apps: state of the art, concerns, regulatory control and certification, Online J. Public Health Inform. 5 (2014) 229. doi:10.5210/ojphi.v5i3.4814. 10. Eye Exercises - Eye Care Plus - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.eyeexamtest.eyecareplus (accessed February 20, 2016). 11. Hearing test - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.geniamedia.pruebaaudicion (accessed February 20, 2016). 12. Blood Pressure Diary - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=org.fruct.yar.bloodpressurediary&hl=en (accessed February 20, 2016). 13. CarePlan inmenteAndroid Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=dk.emergency.inmente (accessed February 20, 2016). 14. Hear - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.denvercs.hear (accessed February 20, 2016). 15. Sleep Help. - iTunes store, (n.d.). https://itunes.apple.com/EN/app/auxiliar-de-dormir/id647567185?mt=8 (accessed February 20, 2016). 16. AAC speech communicator - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.epfl.android.aac_speech (accessed February 20, 2016). 17. Nutrition Facts - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=nutrition.facts.guide (accessed February 20, 2016). 18. In Case of Emergency (ICE): Preparations for a medical emergency - Home Instead Senior Care - iTunes store, (n.d.). https://itunes.apple.com/en/app/in-case-emergency-ice-preparations/id597857196?mt=8 (accessed February 20, 2016). 19. BPSD Guide - Dementia - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=au.edu.unsw.bpsdapp (accessed February 20, 2016). 20. Tecla, Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=ca.idi.tekla (accessed February 20, 2016). 21. TruLink Hearing Control para iPhone, iPod touch e iPad na App Store no iTunes, (n.d.). https://itunes.apple.com/pt/app/trulink-hearingcontrol/id775168025?mt=8 (accessed February 20, 2016). 22. Cardiio - Heart Rate Monitor + 7 Minute Workout Exercise Routine for Cardio Health and Fitness - iTunes store, (n.d.). https://itunes.apple.com/en/app/cardiio-heart-rate-monitor/id542891434?mt=8 (accessed February 20, 2016). 23. Pacer - Pedometer plus Weight and BMI Management and Blood Pressure Tracker, App Store. (n.d.). https://itunes.apple.com/pt/app/pacerpedometer-plus-weight/id600446812?mt=8 (accessed February 20, 2016). 24. Med Helper Pill Reminder - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.earthflare.android.medhelper.lite (accessed February 20, 2016). 25. Eyes Protector Bluelight - Android Apps on Google Play, (n.d.). https://play.google.com/store/apps/details?id=com.ej.easily.bl2 (accessed February 20, 2016).