[{"command":"openDialog","selector":"#drupal-modal","settings":null,"data":"\u003Cdiv id=\u0022republish_modal_form\u0022\u003E\u003Cform class=\u0022modal-form-example-modal-form ecl-form\u0022 data-drupal-selector=\u0022modal-form-example-modal-form\u0022 action=\u0022\/en\/article\/modal\/6233\u0022 method=\u0022post\u0022 id=\u0022modal-form-example-modal-form\u0022 accept-charset=\u0022UTF-8\u0022\u003E\u003Cp\u003EHorizon articles can be republished for free under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.\u003C\/p\u003E\n \u003Cp\u003EYou must give appropriate credit. We ask you to do this by:\u003Cbr \/\u003E\n 1) Using the original journalist\u0027s byline\u003Cbr \/\u003E\n 2) Linking back to our original story\u003Cbr \/\u003E\n 3) Using the following text in the footer: This article was originally published in \u003Ca href=\u0027#\u0027\u003EHorizon, the EU Research and Innovation magazine\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003ESee our full republication guidelines \u003Ca href=\u0027\/horizon-magazine\/republish-our-stories\u0027\u003Ehere\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003EHTML for this article, including the attribution and page view counter, is below:\u003C\/p\u003E\u003Cdiv class=\u0022js-form-item form-item js-form-type-textarea form-item-body-content js-form-item-body-content ecl-form-group ecl-form-group--text-area form-no-label ecl-u-mv-m\u0022\u003E\n \n\u003Cdiv\u003E\n \u003Ctextarea data-drupal-selector=\u0022edit-body-content\u0022 aria-describedby=\u0022edit-body-content--description\u0022 id=\u0022edit-body-content\u0022 name=\u0022body_content\u0022 rows=\u00225\u0022 cols=\u002260\u0022 class=\u0022form-textarea ecl-text-area\u0022\u003E\u003Ch2\u003E\u0027Smartwatch\u0027 sensors to help diagnose depression\u003C\/h2\u003E\u003Cp\u003EScientists in the UK and US are conducting clinical trials with depressed patients, using ultra-sensitive wrist and ankle sensors, detecting tiny fluctuations in emotional arousal.\u003C\/p\u003E\u003Cp\u003E\u2018Psychiatry is 30 to 40 years behind physical health, especially in terms of diagnosis,\u2019 said Dr Szymon Fedor, who received a Marie Sk\u0142odowska-Curie grant to research the potential of depression monitoring at the Massachusetts Institute of Technology in the US.\u003C\/p\u003E\u003Cp\u003E\u2018In physical health we are using blood pressure to predict heart attacks, but in mental health we tend to base it on verbal reports from patients.\u003C\/p\u003E\u003Cp\u003E\u2018We want to be more objective and accurate with diagnosis and treatment of mental health - as we are with heart attacks or strokes.\u2019\u003C\/p\u003E\u003Cp\u003EDr Fedor is running a trial with five depressed patients who are receiving either electroconvulsive therapy or transcranial magnetic stimulation.\u003C\/p\u003E\u003Cp\u003EElectroconvulsive therapy\u0026nbsp;induces seizures in patients to provide relief from symptoms of depression while transcranial magnetic stimulation\u0026nbsp;uses magnetic fields to stimulate nerve cells in the brain.\u003C\/p\u003E\u003Cp\u003EPatients in the study receive the treatments each day for two months while agreeing to wear sensors continuously on their wrists.\u003C\/p\u003E\u003Cp\u003EThe devices measure electrodermal activity - electrical characteristics of the skin that reflect levels of emotional arousal.\u003Cblockquote class=\u0022tw-text-center tw-text-blue tw-font-bold tw-text-2xl lg:tw-w-1\/2 tw-border-2 tw-border-blue tw-p-12 tw-my-8 lg:tw-m-12 lg:tw--ml-16 tw-float-left\u0022\u003E\n \u003Cspan class=\u0022tw-text-5xl tw-rotate-180\u0022\u003E\u201c\u003C\/span\u003E\n \u003Cp class=\u0022tw-font-serif tw-italic\u0022\u003E\u2018The sooner you realise that someone\u2019s behaviour is changing, the sooner someone can make an intervention.\u2019\u0026amp;nbsp;\u003C\/p\u003E\n \u003Cfooter\u003E\n \u003Ccite class=\u0022tw-not-italic tw-font-normal tw-text-sm tw-text-black\u0022\u003EDr Szymon Fedor, Massachusetts Institute of Technology, US\u003C\/cite\u003E\n \u003C\/footer\u003E\n\u003C\/blockquote\u003E\n\u003C\/p\u003E\u003Cp\u003EThe sensors, which look like smartwatches, also pick up heart rate and skin temperature, as well as recording\u0026nbsp;movement - providing data on sympathetic nervous system activity, exercise and sleep.\u003C\/p\u003E\u003Cp\u003EAt the end of each day, participants are asked to download the information from the sensors into a web application on a tablet or smartphone, which is then forwarded to researchers.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAlgorithms\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe physiological data is interpreted with the help of specially developed algorithms, calculating wellbeing, treatment efficacy and risk of relapse.\u003C\/p\u003E\u003Cp\u003EDepression is further evaluated by a clinician, twice weekly, and questions are sent to participants on their smartphones to see whether the physiological measures are corroborated by subjective experience.\u003C\/p\u003E\u003Cp\u003E\u2018By looking at different aspects of a person\u2019s life we can get a more accurate picture of their mood,\u2019 Dr Fedor explained.\u003C\/p\u003E\u003Cp\u003E\u2018We can begin to build the bridge between the diagnosis of mental health conditions and physical diseases.\u2019\u003C\/p\u003E\u003Cp\u003EAlthough individuals in the current study have to download the data at the end of each day, Dr Fedor says live streaming of information will also be possible.\u003C\/p\u003E\u003Cp\u003E\u2018Live streaming could be especially helpful when dealing with individuals who are at risk of suicide,\u2019 Dr Fedor said.\u003C\/p\u003E\u003Cp\u003E\u2018The sooner you realise that someone\u2019s behaviour is changing, the sooner someone can make an intervention.\u003C\/p\u003E\u003Cp\u003E\u2018For example, when the composition of an individual\u2019s anti-depressant drugs is changed, this can initially have adverse effects on behaviour.\u003C\/p\u003E\u003Cp\u003E\u2018They may become very agitated or anxious - the data will show early warning signs for this.\u2019\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EMovement disorder\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOne condition which has been linked to suicide, and particularly the taking of anti-depressant medication, is the movement disorder akathisia.\u003C\/p\u003E\u003Cp\u003EThe condition is linked to increased levels of the neurotransmitter norepinephrine, leading individuals to feel restless and agitated, sometimes rocking back and forth and stamping their legs.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022http:\/\/journals.plos.org\/plosmedicine\/article?id=10.1371\/journal.pmed.0030372\u0022 target=\u0022_blank\u0022\u003EStudies\u003C\/a\u003E have shown that individuals on certain anti-depressant medications \u2013 known as SSRIs - are 10 times as likely to experience the distressing symptoms of akathisia than others.\u003C\/p\u003E\u003Cp\u003E\u2018The sensors will allow researchers to detect when individuals are experiencing akathisia and to act quickly, as this has been linked to suicidal ideation,\u2019 Dr Fedor said.\u003C\/p\u003E\u003Cp\u003E\u2018The sensors will be able to tell when individuals are pacing about or sleeping, for example.\u2019\u003C\/p\u003E\u003Cp\u003EDr Fedor\u0027s project, known as PERSONA, runs until 2017 and follows on from the EU-funded PSYCHE project, which ended in 2013.\u003C\/p\u003E\u003Cp\u003EThis project looked specifically at individuals with bipolar disorder, using physiological data obtained from electronic devices contained within clothing to detect changes in mood.\u003C\/p\u003E\u003C\/textarea\u003E\n\u003C\/div\u003E\n\n \u003Cdiv id=\u0022edit-body-content--description\u0022 class=\u0022ecl-help-block description\u0022\u003E\n Please copy the above code and embed it onto your website to republish.\n \u003C\/div\u003E\n \u003C\/div\u003E\n\u003Cinput autocomplete=\u0022off\u0022 data-drupal-selector=\u0022form-v7c-g0peicmf8e7zm3gbtlfk5mdfvppykelu-gpnbrs\u0022 type=\u0022hidden\u0022 name=\u0022form_build_id\u0022 value=\u0022form-V7C_g0peicmf8e7zM3GBTLfK5MDfvPpYKelu_GPnbRs\u0022 \/\u003E\n\u003Cinput data-drupal-selector=\u0022edit-modal-form-example-modal-form\u0022 type=\u0022hidden\u0022 name=\u0022form_id\u0022 value=\u0022modal_form_example_modal_form\u0022 \/\u003E\n\u003C\/form\u003E\n\u003C\/div\u003E","dialogOptions":{"width":"800","modal":true,"title":"Republish this content"}}]