Projects:2015s1-36 Heartbeat Perception App
- Prof. Mathias Baumert - Dr. Damith Ranasinghe
- Hong Wei TEO - Siok Teng LOKE
The purpose of the project is to develop an Android OS based Heartbeat Perception app with capability of assessing subjects with heartbeat perception task and clinical mental questionnaires as well as providing assessment performance of the subjects to medical authorities to allow them to diagnose the subjects with potential mental symptoms (anxiety, depression, panic attack and etc.). The heart rate monitor shall be used to detect subjects’ heart rate and send this information to Android devices to allow the subjects to conduct the assessment on the devices.
The following project allows identification and understanding of the relationship between human's heart and brain when an individual is undergoing a certain emotional states. This is because individual differences in intensity of emotional experience reflect variation in sensitivity to internal bodily responses. The internal body organ that responses during emotional states are human's heart and brain. There are information signals transmitting from heart to brain’s part called right anterior insular when an individual is undergoing emotional experience (angry, sad, depressed and others). The heartbeat perception app allows user to identify mental symptoms of an individual through clinical mental questionnaire and heartbeat detection task. These two methods provide faster and easier method to identify negative mental symptoms (eating disorder, panic disorder, anxiety, depressions and others) rather than using blood testing and medication testing to identify individual's negative mental symptoms. The following project will benefit the medical community because a faster and easier method is provided for medical doctors to identify individual's early stage of negative mental symptoms in short amount of time. This method can prevent the possibilities of negative mental symptoms of the individual for getting worsens if the symptoms is not traced as soon as possible. Besides that, a better mental symptoms test is needed for now rather than relying on medical pills testing. This is because medical pills testing not only does provide a slower way to identify the symptoms, but also may lead to individual's symptoms worsen or harmed to individual's body if wrong medical pills is given by medical doctors.
The project's final deliverables shall have a complete simple Android software interface that will be working on Android OS mobile device. The apps shall be able to require user to input their personal information (name, gender, height, weight and etc.) and store on the app’s database. Then, the app shall allow user to assess heart rate tracking task to retrieve their heart rate result. Clinical mental questionnaires will be given to assess the user after the heartbeat interoception task. Lastly, mental symptoms result will be given to authorized administrator (doctor) only to show if the user has potential negative mental symptoms. Both heartbeat interoception task and clinical questionnaires data results will be shown alongside with mental symptoms result. On the heartbeat detection side, the project's final deliverables shall allow the mobile device to communicate with heart rate monitor device wirelessly in order to allow the operation of heartbeat interoception tasks.
- Nexus 7 Android OS Tablet - Zephyr HxM BT Heart rate Monitor - Android Studio for Android OS Development
Project Related Works
There are several researches have conducted researches regarding heartbeat perception awareness and human's emotion. First of all, researcher Hugo D. Critchley and his research team stated that negative mental symptoms can be identified through accuracy of heartbeat interoceptive awareness and activity on right anterior insular by assessing an individual on heartbeat perception task and clinical mental questionnaires. In the following research article, researchers have conducted both heartbeat perception tasks method on human that is heartbeat tracking task, individual is asked to count their own heartbeat in a quiet room and heartbeat discrimination task, individual is asked to distinguish their own heartbeat by listening to their own heartbeat. At the same time, the brain activity is measured by fMRI during the pereption task. Then, individual is assessed with clinical mental questionnaires and then, blood pressure of the individual is measured. By referring to these tasks result, researchers founded that negative mental emotion is correlated with both brain activity and heartbeat perception task accuracy and thus, higher interoceptive awareness individual is more vulnerable to negative mental symptoms.
Next, research articles by researcher Rainer Schandry stated that heartbeat interoceptive awareness is correlated to negative mental emotion. In the article, similar methods to Hugo D. Critchley's research article methods are conducted which is heartbeat perception task and clinical mental questionnaires are taken without brain activity measurement. The results showed that negative mental symptoms could be identified through clinical mental questionnaires and heartbeat perception task. A clinical mental questionnaire is commonly used in clinics and hospitals to identify patients’ potential mental symptoms before distributing medicines to patients. The advantage of the mental questionnaires is that it provides a faster method in diagnosing potential mental symptoms and it is safer than medicine pills testing method. The drawback of mental questionnaire is one set of questionnaire is able to identify single mental questionnaires only. Thus, patient is required to assess multiple questionnaires to identify patient’s mental symptoms. Besides that, the mental questionnaires could not provide accurate mental symptoms if the patient did not assess the questionnaires seriously. Heartbeat interoception task consists of both heartbeat tracking task and heartbeat discrimination task. According to the research article’s research results by Rainer Schandry, heartbeat discrimintation task provides more accurate result than heartbeat tracking task. However, both heartbeat interoception tasks are included in the project for better accuracy after decision are made during a supervisor and group members meeting. Thus, this project will integrate all of the task methods which are both heartbeat interoception task and clinical mental questionnaires into the software Android app to assess the individual to identify the possible mental symptoms on the individual. This project will provide easier and faster method than the tasks stated in those research articles to identify individual's negative mental symptoms.
Heartbeat Perception Task
Heartbeat perception task is the main functionality of this project where it assesses the ability of a human to perceive their heartbeat and provide assessments results to the authorities to allow them to identify potential mental symptoms of the subject alongside with clinical mental questionnaires assessments result. In this project, there are two different heartbeat perception tasks known as heartbeat tracking task and heartbeat discrimination task.
Heartbeat Tracking Task is an assessment to allow user or subject to count their number of heartbeat within the specific duration by concentrating on bodily feelings associated with heart actions. Zephyr HxM BT shall count subject’s number of heartbeat at the same time where the counted heartbeat number is stored to compare with subject’s counted heartbeat number to identify the subject’s assessment performance.Heartbeat tracking task is a heartbeat perception method developed by researcher Rainer Schandry for his research article called “Heartbeat Perception and emotional experience” .
In the project, Zephyr HxM BT is used as heart rate monitor and Google Nexus 7 is used as assessment software user interface and assessment result storage for heartbeat tracking task. The heartbeat tracking task for the project consists of 10 trials per task with 30 seconds heartbeat number counting duration for each trial. The 10 trials per task decision is made up after discussion with project supervisor, Professor Mathias where 10 trials per task duration is not too long which may cause frustration from the user and subject and at the same time it is able to provide sufficient data results for medical authorities to identify the subject’s assessment performance for subject’s mental symptoms identification.
A tone with 800Hz frequency and 100ms duration created from Matlab is used to notify user or subject to start and stop counting their heartbeat number. Thus, the subject and Zephyr HxM BT has to start counting subject’s heartbeat number when the start tone is emitted via Nexus 7’s speaker and to stop counting subject’s heartbeat number when stop tone is emitted. After completion of each trial, subject is required to input their estimated heartbeat number into the given input box on the user interface of the app for result storage. After the completion of 10 trials by the subject, the heart rate monitor counted heartbeat number and subject’s estimated heartbeat number are stored and a text file is created with the content of stored counted and estimated heartbeat number results.
Heartbeat Discrimination Task is an assessment to allow user or subject to identify or determine if the emitted heartbeat tones via devices speakers is synchronous or asynchronous with their real heartbeats. The heartbeat tones is made up of 10 beeping tones triggered by the subject heartbeat occurred times detected by the heart rate monitor, Zephyr HxM BT. However, there are two different heartbeat tones that are:
• Synchronous delay interval tones: the tones is synchronous with the subject’s heartbeats; the subject’s real heartbeat tones.
• Asynchronous delay interval tones: the tones is not synchronous with the subject’s heartbeats; the subject’s false heartbeat tones.
The synchronous and asynchronous delay interval tones are played randomly throughout the task and the subject has to identify which one is their heartbeat tones, the synchronous heartbeat tones. For more information about synchronous and asynchronous delay interval tones, please refer to Appendix B with the heartbeat tones figure. In the project, the heartbeat discrimination tasks is developed from combination of two different heartbeat discrimination task methods called Brener & Klutvitse method and Whitehead method.In a research article called “Facilitation of heartbeat self-perception in a discrimination task with individual adjustment of the S+ delay values” by author Alberto Acosta Mesas a and Joaqu´ın Pegalajar Chica, the article suggested to use Brener and Kluvitse (BK) method to identify each subject’s heartbeat perception delay intervals and use the respective delay intervals to apply into Whitehead task where the delay interval from Brener and Kluvitse (BK) method will be synchronous delay (S+) and asynchronous delay will be S+ plus 300ms .
The heartbeat discrimination task for the project is the combination of BK method and Whitehead method. The combination of two different task methods decision is based on the reference to the several research articles related to heartbeat discrimination task and the discussion with the project supervisors during weekly meeting. In the heartbeat discrimination task, the user or subject are required to assess BK method first then only Whitehead method due to BK method is used to identify subject’s heartbeat perception delay intervals and use the respective delay intervals to apply into Whitehead method. In the whitehead method, there are two different heartbeat tones that are:
• Synchronous delay interval tones
It is the subject’s real heartbeat tones where the delay interval = subject’s chosen delay interval + subject’s R-to-R interval from heartbeat
• Asynchronous delay interval tones It is the subject’s false heartbeat tones where the delay interval = subject’s chosen delay interval + subject’s R-to-R interval from heartbeat + 300ms
The heartbeat discrimination task in the project is started with the subject to assess BK method which consists of 6 different delay intervals (range: 0-500ms; 100ms steps) heartbeat tones (10 tones, 800Hz frequency, 100ms duration) represented with 6 independent buttons and the subject is allowed to play the heartbeat tones for unlimited times. Then, the subject is required to choose the respective delay interval heartbeat tones that is synchronous with their heartbeat sensations. Next, the subject is required to assess Whitehead method which consists of 10 trials per task. For each trial, subject has to listened to the heartbeat tones (10 tones, 800Hz frequency, 100ms duration) that is either synchronous or asynchronous delay interval randomised by the app. Then, the subject is required to identify the heartbeat tones by choosing TRUE (synchronous with heartbeat) or FALSE (asynchronous with heartbeat) from the drop down input list from the assessment software user interface. By the end of the task, the subject’s estimated result and the actual heartbeat tones result are stored and a text file is created with the content of stored estimated and actual heartbeat tones results.
Clinical Mental Questionnaires
The clinical mental questionnaires in the project is an assessment to identify the subject’s score on the clinical mental symptoms questionnaires which is used to provide reference to the medical authorities regarding the subject’s health status and to allow them to identify subject’s potential mental symptoms apart from based on the heartbeat perception tasks assessment results. There are 3 different clinical mental questionnaires which are General health, Hamilton Anxiety rating scale (HAM-A) and Beck Depression Inventory (BDI) where each of the questionnaires consists of questions related to body health, anxiety disorder and depression.
R. Schandry, 'Heart Beat Perception and Emotional Experience', Psychophysiology, vol. 18, no. 4, pp. 483-488, 1981.
A. Mesas and J. Chica, 'Facilitation of heartbeat self-perception in a discrimination task with individual adjustment of the S+ delay values', Biological Psychology, vol. 65, no. 1, pp. 67-79, 2003.