Investigating Gyroscope Sway Features, Normalization, and Personalization in Detecting Intoxication in Smartphone Users

Alcohol abuse is the third leading lifestyle-related cause of death for individuals in the United States, causing 88,000 deaths each year in the United States from 2006-2010. Existing smartphone applications allow users to manually record their alcohol consumption or take cognitive tests to estimate intoxication levels; however, no smartphone application passively determines one\u27s level of intoxication. After gathering smartphone sensor data from 34 intoxicated subjects, we generated time and frequency domain features such as sway area (gyroscope) and cadence (accelerometer), which were then classified using a supervised machine learning framework. Other novel contributions explored include feature normalization to account for differences in walking styles and automatic outlier elimination to reduce the effect of accidental falls by identifying and removing the top and bottom of a chosen percentage of the data. Various machine learning classifier types such as Random Forest and Bayes Net were compared, and J48 classifier was the most accurate, classifying user gait patterns into BAC ranges of [0.00-0.08), [0.08-0.15), [0.15-0.25), [0.25+) with an accuracy of 89.45%. This best performing classifier was used to build an intelligent smartphone app that will detect the user\u27s intoxication level in real time

Smartphone Gait Inference

An Android smartphone app was developed to determine alcohol intoxication levels based on a user’s gait. It uses the phone\u27s accelerometer to detect differences in gait associated with varying alcohol ingestion levels. Signal analysis found features in the time and frequency domain indicative of intoxication levels. Machine learning methods were employed with these features, trained on data from subjects, and compared by performance on a validation set. The Random Forest method was the best classifier with a success rate of 56% on the training set and 70% on the validation set. The app was distributed for user testing and included the model to be trained with the user’s new data. Accuracy improved overall with the users to 57%. As the app is used more, the accuracy is expected to increase

IntoxiGait Deep Learning

Alcohol abuse has been a pervasive problem worldwide, causing 88,000 annual deaths. Recently, several projects have attempted to estimate a users level of intoxication by measuring gait using mobile sensors. The goal of this project was to compare a deep learning approach to previous methods to predict the blood alcohol concentration of a user by training a convolutional neural network and creating a mobile app which could accurately determine intoxication level. We gathered data from 38 participants over the course of 12 weeks, collecting accelerometer and gyroscope data simultaneously from both a smartwatch and smartphone. Our neural networks accuracy is roughly 64% on the test set and 69% on the training set into 5 BAC ranges for an input containing two seconds of data

Realize, Analyze, Engage (RAE): A Digital Tool to Support Recovery from Substance Use Disorder

Background: Substance use disorders are a highly prevalent group of chronic diseases with devastating individual and public health consequences. Current treatment strategies suffer from high rates of relapse, or return to drug use, and novel solutions are desperately needed. Realize Analyze Engage (RAE) is a digital, mHealth intervention that focusses on real time, objective detection of high-risk events (stress and drug craving) to deploy just-in-time supportive interventions. The present study aims to (1) evaluate the accuracy and usability of the RAE system and (2) evaluate the impact of RAE on patient centered outcomes. Methods: The first phase of the study will be an observational trial of N = 50 participants in outpatient treatment for SUD using the RAE system for 30 days. Accuracy of craving and stress detection algorithms will be evaluated, and usability of RAE will be explored via semi-structured interviews with participants and focus groups with SUD treatment clinicians. The second phase of the study will be a randomized controlled trial of RAE vs usual care to evaluate rates of return to use, retention in treatment, and quality of life. Anticipated findings and future directions: The RAE platform is a potentially powerful tool to de-escalate stress and craving outside of the clinical milieu, and to connect with a support system needed most. RAE also aims to provide clinicians with actionable insight to understand patients\u27 level of risk, and contextual clues for their triggers in order to provide more personalized recovery support

Mapping and analysis of user-accesible mobile applications focused on reducing alcohol consumption

Backgroud: Modern technology is developing quite fast on every level of many systems. For example the implementation of eHealth to national strategies and the implementation of technology tools in a care health system or in specialized services. Today, mobile phone are readily available and enhanced and mobile technology is en example of medium that is used in everyday life. Mobile applications (apps) aiming on reduction of alcohol consumption are nowadays observably more available on the market but their effectiveness and evaluation is still unclear. Aim: The main aim of this study is to map selected user-accessible applications available for reduction of alcohol consumption available on digital distribution services of the Android and iOS mobile systems and to describe their basic features. Methods: The study combines content analysis of provided features and functions of user-accessible mobile applications for reduction of alcohol consumption and user testing of a total of four applications. A self-assessment tool was developed for the testing purposes. The tools described the application in the specified categories (basic technical specifications, design, software, techniques and interventions for the reduction of alcohol consumption). Two Android apps and two iOS apps that met predefined...Východiska: Moderní technologie jsou odvětvím, které se rozvíjí velice rychle a na úrovních všech systémů. Příkladem je také implementace eHealth do strategií států a implementace technologických nástrojů v péči o klienty v odborných službách i mimo ně. Mobilní telefony jsou dnes snadno dostupné a velmi rozšířené, a mobilní technologie jsou příkladem nástroje, který je zároveň využíván také v každodenním životě. Na trhu se objevuje stále více dostupných mobilních aplikací zaměřených na redukci konzumace alkoholu, avšak není stále vyjasněna jejich efektivita a hodnocení. Cíl: Hlavním cílem práce je zmapovat vybrané volně dostupné mobilní aplikace se zaměřením na redukci konzumace alkoholu v distribučních platformách systémů Android a iOS a popsat jejich vlastnosti a funkcionality. Metody: Práce využívá kombinace obsahové analýzy vlastností a funkcí volně dostupných mobilních aplikací zaměřených na redukci konzumace alkoholu a uživatelského testování celkem čtyř aplikací. Pro účely testování byl vytvořen vlastní posuzovací nástroj, který aplikace popisoval ve stanovených kategoriích (základních technických informací, designu, software, techniky a intervence pro redukci konzumace alkoholu). Pro uživatelské testování byly vybrány dvě aplikace v systému Android a dvě aplikace v systému iOS, které...Klinika adiktologie 1.LF UK a VFN v PrazeDepartment of Adictology First Faculty of Medicine and General University Hospital in PragueFirst Faculty of Medicine1. lékařská fakult

Physiological-based Driver Monitoring Systems: A Scoping Review

A physiological-based driver monitoring system (DMS) has attracted research interest and has great potential for providing more accurate and reliable monitoring of the driver’s state during a driving experience. Many driving monitoring systems are driver behavior-based or vehicle-based. When these non-physiological based DMS are coupled with physiological-based data analysis from electroencephalography (EEG), electrooculography (EOG), electrocardiography (ECG), and electromyography (EMG), the physical and emotional state of the driver may also be assessed. Drivers’ wellness can also be monitored, and hence, traffic collisions can be avoided. This paper highlights work that has been published in the past five years related to physiological-based DMS. Specifically, we focused on the physiological indicators applied in DMS design and development. Work utilizing key physiological indicators related to driver identification, driver alertness, driver drowsiness, driver fatigue, and drunk driver is identified and described based on the PRISMA Extension for Scoping Reviews (PRISMA-Sc) Framework. The relationship between selected papers is visualized using keyword co-occurrence. Findings were presented using a narrative review approach based on classifications of DMS. Finally, the challenges of physiological-based DMS are highlighted in the conclusion. Doi: 10.28991/CEJ-2022-08-12-020 Full Text: PD

Proposal of a Clinical Practice Guideline for a Non-Pharmacologic Music Listening Complementary Pain Therapy

Background: As many as 65% of post-surgical patients experience moderate to severe pain. Post-surgical pain is associated with a variety of negative physical and psychological consequences for patients. Currently, medical treatments for postoperative pain rely heavily on pharmaceuticals which can cause adverse side effects. Opioid analgesics, most notably, cause hypoventilation, apnea, and in some cases, dependence and addiction. In 2017, in response to state and national opioid prescription reduction programs, The Joint Commission (TJC) began requiring healthcare institutions to provide patients with non-pharmacologic pain treatment modalities. These pain treatment modalities, also known as complementary therapies, include music listening interventions, which have been shown to safely decrease pain in postoperative patients. The analgesic benefits of music have been measured in numerous controlled trials and meta-analyses. Problem: The culmination of over 30 stakeholder reports and direct observations by the project team revealed that a midwestern level-1 trauma medical center has been unable to meet TJC’s requirement to provide postoperative patients with the required non-pharmacologic pain therapies. This inspired a policy search at the healthcare facility of interest which revealed that no policy currently exists that dictates the provision of non-pharmacologic complementary therapy to patients. Purpose: The ultimate purpose of this project is to identify, adapt, and recommend an evidence-based clinical practice guideline for a postoperative music listening intervention to meet TJC’s requirement for the provision of non-pharmacologic pain treatment modalities at the healthcare facility of interest. Project leaders gathered valuable data and developed recommendations for the leadership groups which have the authority to mitigate, monitor, and sustain non-pharmacological modalities such as music listening at the healthcare facility of interest. Methods: The following objectives and methods are framed using the Plan-Do-Check-Act (PDCA) cycle, also known as the Deming cycle. 1) The project team has reviewed and synthesized evidence from the literature, hospital policy, and TJC accreditation requirements for hospitals to aid in the identification of a guideline for non-pharmacologic complementary pain therapy for patients. The planning phase also included a SWOT analysis discussion with stakeholders and personnel directly caring for patients in the PACU. 2) Members of the project team identified and modified an evidence-based clinical practice guideline from current literature incorporating feedback from the SWOT analysis for future proposal to the healthcare facility of interest. 3) The project team then collaborated with and incorporated feedback on proposed clinical practice guideline from preoperative and PACU leadership, nurses, and other stakeholders involved in the care of postoperative patients. 4) Lastly, the project team presented project findings and the modified evidence-based guideline recommendations to key stakeholders. Implications: This scholarly project can serve as a beginning point towards improving post-surgical patient pain and the medical center’s compliance with TJC requirement for healthcare facilities to provide non-pharmacologic pain treatment modalities by recommending an evidence-based clinical practice guideline for a music listening intervention in the PACU. This project is significant because it can assist the healthcare facility of interest in complying with TJC requirements. The findings of the scholarly project can also assist other departments within the healthcare system in implementing non-pharmacological pain therapy, specifically music listening interventions

Effects of Peritraumatic Alcohol Intoxication on Intrusive Memories Following Exposure to an Analog Trauma

Intrusive memories and associated symptoms of posttraumatic stress disorder (PTSD) represent a significant public health problem, often leading to persistent physical and psychological difficulties experienced by victims long after the traumatic event, contributing to healthcare costs and loss of productivity. Research examining etiological factors that contribute to PTSD is needed in order to expand basic knowledge and to inform the development of prevention and intervention strategies. Although acute alcohol intoxication has the potential to impact established risk factors for the development of intrusive memories (e.g., via stress response, cognitive processing), and trauma—particularly sexual assault—often occurs under the influence of alcohol, the influence of peritraumatic (i.e., at the time of assault) alcohol intoxication on post-assault trauma symptoms is not well understood. To address this issue, the current study utilized an experimental design, including lab-based alcohol administration (high dose of .72 g/kg, low dose of .36 g/kg, and a placebo beverage), a well-accepted analog trauma exposure paradigm (a film with distressing or “traumatic” content), and ecological momentary assessment of intrusive memories. Results from 98 community women (ages 21 to 30, without a personal history of victimization) revealed peritraumatic intoxication did impact the occurrence of intrusive memories. Specifically, a marginally significant indirect effect showed that alcohol myopia disrupted cognitive processing and formation of trauma memories, resulting in increased intrusive memories at high levels of intoxication. At the same time, those who consumed high or low doses of alcohol displayed a dampened stress response, which reduced intrusive memories. Findings highlight the influence of peritraumatic cognitive impairment and stress response on the development of intrusive memories. Though alcohol influenced these risk factors simultaneously and in opposite directions, overall, participants in the high dose condition reported more intrusive memories than those in the placebo and low dose conditions. These findings reflect the importance of prevention and intervention programs aimed at reducing alcohol-involved victimization. Adviser: David DiLill

Participative Urban Health and Healthy Aging in the Age of AI

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems