1) Smart interventions delivered through mobile applications have the potential to overcome obstacles of traditional cognitive behavioral therapy (CBT) by providing real-time, personalized CBT.
2) The company Minddistrict has developed a platform that uses experience sampling data collected through a mobile diary app to provide automated, personalized interventions tailored to each individual's needs and delivered in the moment.
3) Minddistrict's approach involves three stages - from brief assessments and supportive messages, to using correlations to determine personal risk factors and provide insights, to training reinforcement learning algorithms that can adapt interventions over time based on what works best for that individual.
Smart Brain Wave Sensor for Paralyzed- A Real Time ImplementationSiraj Ahmed
ABSTRACT
As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment.
Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.
Jennifer McTigue on New Innovations for Mental HealthJennifer McTigue
Jennifer McTigue says Virtual reality, mobile apps, and other forms of emerging tech are changing how we approach mental health. Recent developments in sensor technologies, online psychological therapies and video remote counseling, mobile apps (apps), and gaming are all providing genuine opportunities to engage and empower patients, and create new approaches both for the assessment and intervention of mental health problems. With the growth of VR, video games are becoming increasingly prevalent, ultimately becoming used even within the context of mental health care.
Video games enable individuals to concentrate on several tasks simultaneously, leading patients to experience measurable improvements in mental wellbeing. As we have mentioned, patients suffering from attention deficit hyperactivity disorder may be able to enhance their attention spans while seated in the virtual reality class, but they may also be able to do this while playing a video game. Evidence shows that the technology is able to identify patients who may experience depression, and also provide treatment if needed. These digital technologies could dramatically increase access to mental health care and adherence to treatment, by allowing services to be delivered in more flexible ways tailored to the needs of the individual patient.
Smart Brain Wave Sensor for Paralyzed- A Real Time ImplementationSiraj Ahmed
ABSTRACT
As the title of the paper indicates about brainwaves and its uses for various applications based on their frequencies and different parameters which can be implemented as real time application with the title a smart brain wave sensor system for paralyzed patients. Brain wave sensing is to detect a person's mental status. The purpose of brain wave sensing is to give exact treatment to paralyzed patients. The data or signal is obtained from the brainwaves sensing band. This data are converted as object files using Visual Basics. The processed data is further sent to Arduino which has the human's behavioral aspects like emotions, sensations, feelings, and desires. The proposed device can sense human brainwaves and detect the percentage of paralysis that the person is suffering. The advantage of this paper is to give a real-time smart sensor device for paralyzed patients with paralysis percentage for their exact treatment.
Keywords:-Brainwave sensor, BMI, Brain scan, EEG, MCH.
Jennifer McTigue on New Innovations for Mental HealthJennifer McTigue
Jennifer McTigue says Virtual reality, mobile apps, and other forms of emerging tech are changing how we approach mental health. Recent developments in sensor technologies, online psychological therapies and video remote counseling, mobile apps (apps), and gaming are all providing genuine opportunities to engage and empower patients, and create new approaches both for the assessment and intervention of mental health problems. With the growth of VR, video games are becoming increasingly prevalent, ultimately becoming used even within the context of mental health care.
Video games enable individuals to concentrate on several tasks simultaneously, leading patients to experience measurable improvements in mental wellbeing. As we have mentioned, patients suffering from attention deficit hyperactivity disorder may be able to enhance their attention spans while seated in the virtual reality class, but they may also be able to do this while playing a video game. Evidence shows that the technology is able to identify patients who may experience depression, and also provide treatment if needed. These digital technologies could dramatically increase access to mental health care and adherence to treatment, by allowing services to be delivered in more flexible ways tailored to the needs of the individual patient.
Life is hard, but it offers progress and satisfaction. It's normal to feel many emotions, and you can cope and feel better. You're supported.
Our mental health app offers 24/7 professional assistance!
We can create a positive mental health graphic by analysing these patterns with machine learning techniques.
These insights can help mental health professionals diagnose, plan, and track treatment.
Our app helps you manage your mental health with guided meditations, mood tracking, and personalised self-care routines.
Our mood tracking function helps you recognise patterns and make positive changes by keeping track of your emotions.
Our guided meditation function allows you to find the right audio and video meditations for you.
Our personalised self-care plans provide information and advice on stress management, sleep quality, and healthy living.
If you need help, our app lets you contact with a licenced therapist.
Our convenient scheduling system lets you pick a time for your session.
Our mental health app helps you to improve your mental health daily.
Download our app today to improve your mental health!
علوم شناختی به طور ساده به صورت «پژوهش علمی دربارهٔ ذهن و مغز» تعریف میشود، شاخهای میانرشتهای است که از رشتههای مختلفی مانند روانشناسی، فلسفه ذهن، عصبشناسی، زبانشناسی، انسانشناسی، علوم رایانه و هوش مصنوعی تشکیل شده است. این علم به بررسی ماهیت فعالیتهای ذهنی مانند تفکر، طبقهبندی و فرایندهای که انجام این فعالیتها را ممکن میکند میپردازد. به صورت مشخص تر از جمله اهداف اصلی این رشته پژوهش در زمینه بینایی، تفکر و استدلال کردن، حافظه، توجه، یادگیری و مباحثی مربوط به زبان میباشد.
The Power of Sensors in health & healthcareD3 Consutling
In a series of reports we explore key digital health trends and related opportunities for technology companies, healthcare providers and patients-consumers. We take both an international and Flemish perspective, the latter based on interviews with local stakeholders. In this report we focus on sensor-based applications.
Mental health: the prefect subject for app useNIHR_MindTech
Prof Chris Hollis from MindTech speaks at the Royal Society of Medicine in April 2016 on healthcare apps about the potential and pitfalls of apps for use within mental health
Depression and anxiety detection through the Closed-Loop method using DASS-21TELKOMNIKA JOURNAL
The change of information and communication technology has brought many changes in daily
life. The way humans interacting is changing. It is possible to express each form of communication directly
and instantly. Social media has contributed data in size, diversity and capacity and quality. Based on it,
the idea was to see and measure the tendency of depression and anxiety through social media using
the Closed-Loop method using Facebook text mining posts. Through the stages of pre-processing
including text extraction using the Naïve Bayes machine learning model for text classification, the early
signs of depression and anxiety are measured using DASS-21 parameter. In total, 22,934 Facebook posts
were contributed as training and learning data collected from July 2017 until July 2018. As a results,
analysis and mapping of social demographics of users that are usually as a trigger of depression, and
anxiety, such as grief, illness, household affairs, children education and others are available.
Mental Health Technology Trends_ The Role Of Technology In Mental Health.pdfLucas Lagone
Explore the latest mental health technology trends. Discover how technology impacts mental fitness. Benefits and challenges of mental health applications on devices and wearables.
Original Source: https://www.nevinainfotech.com/blog/mental-health-technology-trends/
A quick review of Kno.e.sis’ research subset on knowledge-enhanced learning with on personal and public health, wellbeing and social good applications.
Life is hard, but it offers progress and satisfaction. It's normal to feel many emotions, and you can cope and feel better. You're supported.
Our mental health app offers 24/7 professional assistance!
We can create a positive mental health graphic by analysing these patterns with machine learning techniques.
These insights can help mental health professionals diagnose, plan, and track treatment.
Our app helps you manage your mental health with guided meditations, mood tracking, and personalised self-care routines.
Our mood tracking function helps you recognise patterns and make positive changes by keeping track of your emotions.
Our guided meditation function allows you to find the right audio and video meditations for you.
Our personalised self-care plans provide information and advice on stress management, sleep quality, and healthy living.
If you need help, our app lets you contact with a licenced therapist.
Our convenient scheduling system lets you pick a time for your session.
Our mental health app helps you to improve your mental health daily.
Download our app today to improve your mental health!
علوم شناختی به طور ساده به صورت «پژوهش علمی دربارهٔ ذهن و مغز» تعریف میشود، شاخهای میانرشتهای است که از رشتههای مختلفی مانند روانشناسی، فلسفه ذهن، عصبشناسی، زبانشناسی، انسانشناسی، علوم رایانه و هوش مصنوعی تشکیل شده است. این علم به بررسی ماهیت فعالیتهای ذهنی مانند تفکر، طبقهبندی و فرایندهای که انجام این فعالیتها را ممکن میکند میپردازد. به صورت مشخص تر از جمله اهداف اصلی این رشته پژوهش در زمینه بینایی، تفکر و استدلال کردن، حافظه، توجه، یادگیری و مباحثی مربوط به زبان میباشد.
The Power of Sensors in health & healthcareD3 Consutling
In a series of reports we explore key digital health trends and related opportunities for technology companies, healthcare providers and patients-consumers. We take both an international and Flemish perspective, the latter based on interviews with local stakeholders. In this report we focus on sensor-based applications.
Mental health: the prefect subject for app useNIHR_MindTech
Prof Chris Hollis from MindTech speaks at the Royal Society of Medicine in April 2016 on healthcare apps about the potential and pitfalls of apps for use within mental health
Depression and anxiety detection through the Closed-Loop method using DASS-21TELKOMNIKA JOURNAL
The change of information and communication technology has brought many changes in daily
life. The way humans interacting is changing. It is possible to express each form of communication directly
and instantly. Social media has contributed data in size, diversity and capacity and quality. Based on it,
the idea was to see and measure the tendency of depression and anxiety through social media using
the Closed-Loop method using Facebook text mining posts. Through the stages of pre-processing
including text extraction using the Naïve Bayes machine learning model for text classification, the early
signs of depression and anxiety are measured using DASS-21 parameter. In total, 22,934 Facebook posts
were contributed as training and learning data collected from July 2017 until July 2018. As a results,
analysis and mapping of social demographics of users that are usually as a trigger of depression, and
anxiety, such as grief, illness, household affairs, children education and others are available.
Mental Health Technology Trends_ The Role Of Technology In Mental Health.pdfLucas Lagone
Explore the latest mental health technology trends. Discover how technology impacts mental fitness. Benefits and challenges of mental health applications on devices and wearables.
Original Source: https://www.nevinainfotech.com/blog/mental-health-technology-trends/
A quick review of Kno.e.sis’ research subset on knowledge-enhanced learning with on personal and public health, wellbeing and social good applications.
2. Bridging the gap:
Smart interventions to overcome obstacles of
traditional cognitive behavioral therapy
By Maurice Niessen
Research manager, Minddistrict
3. Smart interventions 2
Over the past decade and a half, cognitive behavioural therapy
(CBT) based online interventions have been developed for a wide
variety of mental health disorders. Although effective, these in-
terventions have yet to fully address the limitations of traditional
CBT, known as the ‘knowledge to practice gap’ and the ‘therapy
to real world gap’. Recent innovations however suggest that mo-
bile applications will soon overcome these obstacles by delivering
real-time, personalised CBT.
In the past, mental health professionals that offered traditional face-to-face
CBT to their clients had to overcome the difficulties of personalising CBT
protocols to each client, and assisting the client in implementing cognitive
and behavioural strategies in their everyday lives. Nowadays, therapists are
already much better equipped to reduce the gap between the therapist’s
office and real-life. The modern therapist’s toolbox consists of face-to-face
contacts, video conferencing and secure messaging. In addition, websites
and mobile applications are available to deliver psychological educational
material, homework exercises and diaries. Together, these tools have the
potential to make interventions become a seamless part of day-to-day life
enabling clients to access care whenever and wherever they choose.
Real-time data collection
Recently, there has been an increased focus on investigating experiences
outside the therapy office, in the context in which they are occuring. A
powerful rationale for this approach is provided by a growing awareness
that models of psychopathology are dynamic over time and experiences are
situated. The experience sampling method (ESM) is a data collection strate-
gy in which individuals are asked in normal daily life to report their thoughts,
feelings and symptoms, as well as the context (e.g. location, company,
activity) and their judgement of this context. The reports typically have to be
filled out several times a day, on consecutive days, either at random unpre-
dictable moments, at moments signalled by a beeper or alternatively, trigge-
red by an event of interest. The mobile revolution has propelled ESM studies
over recent years and has triggered some to commence developing ESM
based interventions. Amsterdam based Minddistrict is one of these compa-
nies.
4. Smart interventions 3
Minddistrict
In the Netherlands, two out of three mental health care institutions already
apply ehealth in their care provisions or communication with patients. The
vision of Dutch ehealth market leader Minddistrict is to facilitate lasting be-
havioural change by providing effective and cost-effective, seamless ehealth
solutions. For this purpose, Minddistrict has developed an easy-to-use,
secure online platform in which interventions can be dynamically tailored
to the current needs of an individual client. The platform contains eviden-
ce-based CBT modules for the prevention, early intervention, treatment
and aftercare of a wide variety of mental health disorders which can be
implemented with varying levels of professional guidance (self-help, guided
self-help, psychotherapy). In addition to the treatment modules, screening,
secure messaging and video chat can be offered to the client on his or her
personalised platform which is connected to a mobile diary app.
From insight to automated intervention
The ESM is incorporated into Minddistrict’s diary app. Graphs are included to
provide a detailed insight into the daily course of thoughts, feelings, symp-
toms and their context. Displayed in the diary app, the real-time graphs help
to create awareness for the patient. The therapist is able to view the same
graphs in his or her secure online platform. Recent studies suggest that the
ESM can also be utilised to deliver personalised, automated, in-the-mo-
ment, ‘smart’ interventions. Minddistrict agrees with this assessment and
has outlined its three-stage ‘smart’ intervention development plan. At each
progressing stage, increasing levels of intelligence are added to the inter-
vention.
In the first stage, clients complete a brief assessment of their current emoti-
onal status in response to a random sound trigger on Minddistrict’s mobile
diary app with multiple choice touchscreen response options. The respon-
ses determine the nature of the subsequent intervention they will receive.
Supportive messages are displayed in response to reported negative emoti-
ons and reaffirming thoughts are depicted when the client indicates positive
affect. These automated messages have multiple wording variations so that
clients do not encounter the exact same intervention every time, even if
they make similar selections. Also, all intervention content can be accessed
whenever and wherever clients choose.
In addition, in the second stage, correlations between context and emotions
5. Smart interventions 4
are calculated to determine personal protective and risk factors. To create
awareness, these insights are reported to the user and therapist. Emotion
mining, or the automated identification of emotions by analysing patterns
in users’ texts, is utilised for groups of clients who lack the ability to identify
or decribe their emotional state or situational context. Emotion mining may
also allow for subconscious emotions to be addressed and perhaps even
future emotional states to be predicted. Minddistrict is currently studying the
potential of emotion mining in association with Maastricht University.
In the third stage, the flow of realtime assessment data is used to train a
reinforcement learning algorithm that will adapt the frequency, timing,
content and intervention medium to the unique characteristics of the client.
At this stage, algorithms are utilised that would ‘learn’ which momentary
states predict certain behaviours and which mobile interventions influence
these momentary states in the desired direction.
Smart self-management
An algorithm would for instance ‘learn’ that if during the evening, a certain
client assesses his current self-esteem as less than four out of seven, he is
more likely to abuse alcohol and also that a certain audioclip is most likely
to lift his self-esteem. If in addition, analysis indicated that the user is more
likely to experience low self-esteem on a specific day of the week, the
audioclip may be offered early on those evenings as an attempt to avert low
self-esteem. Reinforcement learning could also occur across individuals,
in which an intervention strategy with the highest probability of reward for
each individual is offered, based on an analysis of what worked best for
previous users of the system with similar assessment data.
Because of the multi-media capabilities of mobile devices, the intelligent,
real-time, interventions may consist of text, audio/video clips, photos and
voice recordings, among other media. Although initially offered with profes-
sional guidance, this smart intervention also allows for a greater degree of
self-management by clients.
Minddistrict is seeking alliances with academia to develop this next genera-
tion of online interventions. Will you join us?
6. References
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for adult depression: a meta-analysis.Cogn Behav Ther. 2009;38(4):196-205.
Andrews G, Cuijpers P, Craske MG, McEvoy P, Titov N. Computer therapy for the anxiety
and depressive disorders is effective, acceptable and practical health care: a meta-analysis.
PLoS One. 2010 Oct 13;5(10):e13196.
Cuijpers P, Marks IM, van Straten A, Cavanagh K, Gega L, Andersson G.
Computer-aided psychotherapy for anxiety disorders: a meta-analytic review.
Cogn Behav Ther. 2009;38(2):66-82.
Kelly J, Gooding P, Pratt D, Ainsworth J, Welford M, Tarrier N. Intelligent real-time the-
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cognitive-behavioural interventions. J Ment Health. 2012;21(4):404-14.
Dutch Association of Mental Health and Addiction Care. E-mental Health in the Nether-
lands. 2013.
Ben-Zeev D, Brenner CJ, Begale M, Duffecy J, Mohr DC, Mueser KT. Feasibility, Accepta-
bility, and Preliminary Efficacy of a Smartphone Intervention for Schizophrenia.
Schizophr Bull. 2014 Mar 19. [Epub ahead of print]
Delespaul PAEG. Assessing Schizophrenia in Daily Life. 1995. Maastricht. University of
Maastricht.
Niamat SC. Impact of eMental Health: a Quantitative Analysis. 2011. Amsterdam. Faculty of
Sceinces, Business Mathematics and Informatics, VU University.
Myin-Germeys I, Birchwood M, Kwapil T. From environment to therapy in psychosis: a
real-world momentary assessment approach. Schizophr Bull. 2011 Mar;37(2):244-7.
Myin-Germeys I, Oorschot M, Collip D, Lataster J, Delespaul P, van Os J. Experience
sampling research in psychopathology: opening the black box of daily life. Psychol Med.
2009 Sep;39(9):1533-47.
Remmel F. Emotion Mining. 2014. Maastricht. Department of Knowledge Engineering, Uni-
versity of Maastricht.
Richters J, Gerrits R. Een pilot studie naar de potentiele effecten van online behandeling
voor verschillende angststoornissen en depressie. Gedragstherapie 2013;46:161-178.
Ruwaard J. The Efficacy and Effectiveness of online CBT. 2013. Amsterdam. Department
of Clinical Psychology, University of Amsterdam.
Smart interventions 5