scholarly journals Automatic Assessment of Loneliness in Older Adults Using Speech Analysis on Responses to Daily Life Questions

2021 ◽  
Vol 12 ◽  
Author(s):  
Yasunori Yamada ◽  
Kaoru Shinkawa ◽  
Miyuki Nemoto ◽  
Tetsuaki Arai
Keyword(s):  
Older Adults ◽  
Early Detection ◽  
Daily Life ◽  
Binary Classification ◽  
Emotional States ◽  
Automatic Assessment ◽  
Adverse Health Effects ◽  
Wide Range ◽  
Speech Data ◽  
Speech Features

Loneliness is a perceived state of social and emotional isolation that has been associated with a wide range of adverse health effects in older adults. Automatically assessing loneliness by passively monitoring daily behaviors could potentially contribute to early detection and intervention for mitigating loneliness. Speech data has been successfully used for inferring changes in emotional states and mental health conditions, but its association with loneliness in older adults remains unexplored. In this study, we developed a tablet-based application and collected speech responses of 57 older adults to daily life questions regarding, for example, one's feelings and future travel plans. From audio data of these speech responses, we automatically extracted speech features characterizing acoustic, prosodic, and linguistic aspects, and investigated their associations with self-rated scores of the UCLA Loneliness Scale. Consequently, we found that with increasing loneliness scores, speech responses tended to have less inflections, longer pauses, reduced second formant frequencies, reduced variances of the speech spectrum, more filler words, and fewer positive words. The cross-validation results showed that regression and binary-classification models using speech features could estimate loneliness scores with an R2 of 0.57 and detect individuals with high loneliness scores with 95.6% accuracy, respectively. Our study provides the first empirical results suggesting the possibility of using speech data that can be collected in everyday life for the automatic assessments of loneliness in older adults, which could help develop monitoring technologies for early detection and intervention for mitigating loneliness.

scholarly journals Tablet-Based Automatic Assessment for Early Detection of Alzheimer's Disease Using Speech Responses to Daily Life Questions

2021 ◽  
Vol 3 ◽  
Author(s):  
Yasunori Yamada ◽  
Kaoru Shinkawa ◽  
Masatomo Kobayashi ◽  
Masafumi Nishimura ◽  
Miyuki Nemoto ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Health Monitoring ◽  
Daily Life ◽  
Automatic Assessment ◽  
Early Signs ◽  
Speech Features ◽  
Neuropsychological Tasks ◽  
Monitoring Technologies

Health-monitoring technologies for automatically detecting the early signs of Alzheimer's disease (AD) have become increasingly important. Speech responses to neuropsychological tasks have been used for quantifying changes resulting from AD and differentiating AD and mild cognitive impairment (MCI) from cognitively normal (CN). However, whether and how other types of speech tasks with less burden on older adults could be used for detecting early signs of AD remains unexplored. In this study, we developed a tablet-based application and compared speech responses to daily life questions with those to neuropsychological tasks in terms of differentiating MCI from CN. We found that in daily life questions, around 80% of speech features showing significant differences between CN and MCI overlapped those showing significant differences in both our study and other studies using neuropsychological tasks, but the number of significantly different features as well as their effect sizes from life questions decreased compared with those from neuropsychological tasks. On the other hand, the results of classification models for detecting MCI by using the speech features showed that daily life questions could achieve high accuracy, i.e., 86.4%, comparable to neuropsychological tasks by using eight questions against all five neuropsychological tasks. Our results indicate that, while daily life questions may elicit weaker but statistically discernable differences in speech responses resulting from MCI than neuropsychological tasks, combining them could be useful for detecting MCI with comparable performance to using neuropsychological tasks, which could help develop health-monitoring technologies for early detection of AD in a less burdensome manner.

scholarly journals Age-Related Differences in the Perception of Eye-Gaze from a Social Robot

2021 ◽  
Author(s):  
Lucas Morillo Mendez ◽  
Martien GS Schrooten ◽  
Amy Loutfi ◽  
Oscar Martinez Mozos
Keyword(s):  
Older Adults ◽  
Social Perception ◽  
Daily Life ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Facilitation Effect ◽  
Verbal Cues ◽  
Younger Adults ◽  
Age Related ◽  
Wide Range

The sensibility to deictic gaze declines naturally with age and often results in reduced social perception. Thus, the increasing efforts in developing social robots that assist older adults during daily life tasks need to consider the effects of aging. In this context, as non-verbal cues such as deictic gaze are important in natural communication in human-robot interaction, this paper investigates the performance of older adults, as compared to younger adults, during a controlled, online (visual search) task inspired by daily life activities, while assisted by a social robot.This paper also examines age-related differences in social perception. Our results showed a significant facilitation effect of head movement representing deictic gaze from a Pepper robot on task performance. This facilitation effect was not significantly different between the age groups. However, social perception of the robot was less influenced by its deictic gaze behavior in older adults, as compared to younger adults. This line of research may ultimately help informing the design of adaptive non-verbal cues from social robots for a wide range of end users.

DSM-5 alcohol use disorder features among treatment-seeking older adults

2018 ◽  
Vol 64 (4) ◽  
pp. 185-196 ◽  
Author(s):  
Silke Behrendt ◽  
Barbara Braun ◽  
Randi Bilberg ◽  
Gerhard Bühringer ◽  
Michael Bogenschutz ◽  
...  
Keyword(s):  
Older Adults ◽  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
The Elderly ◽  
Treatment Seeking ◽  
Controlled Clinical Trial ◽  
Dsm 5 ◽  
Wide Range ◽  
And Gender ◽  
International Multicenter

Abstract. Background: The number of older adults with alcohol use disorder (AUD) is expected to rise. Adapted treatments for this group are lacking and information on AUD features in treatment seeking older adults is scarce. The international multicenter randomized-controlled clinical trial “ELDERLY-Study” with few exclusion criteria was conducted to investigate two outpatient AUD-treatments for adults aged 60+ with DSM-5 AUD. Aims: To add to 1) basic methodological information on the ELDERLY-Study by providing information on AUD features in ELDERLY-participants taking into account country and gender, and 2) knowledge on AUD features in older adults seeking outpatient treatment. Methods: baseline data from the German and Danish ELDERLY-sites (n=544) were used. AUD diagnoses were obtained with the Mini International Neuropsychiatric Interview, alcohol use information with Form 90. Results: Lost control, desired control, mental/physical problem, and craving were the most prevalent (> 70 %) AUD-symptoms. 54.9 % reported severe DSM-5 AUD (moderate: 28.2 %, mild: 16.9 %). Mean daily alcohol use was 6.3 drinks at 12 grams ethanol each. 93.9 % reported binging. More intense alcohol use was associated with greater AUD-severity and male gender. Country effects showed for alcohol use and AUD-severity. Conclusion: European ELDERLY-participants presented typical dependence symptoms, a wide range of severity, and intense alcohol use. This may underline the clinical significance of AUD in treatment-seeking seniors.

Assessment of health related issues in individuals’, couples’, and families’ daily life

2008 ◽  
Vol 16 (3) ◽  
pp. 146-149 ◽  
Author(s):  
Meinrad Perrez ◽  
Michael Reicherts ◽  
Yves Hänggi ◽  
Andrea B. Horn ◽  
Gisela Michel ◽  
...  
Keyword(s):  
Emotion Regulation ◽  
Daily Life ◽  
Ecological Validity ◽  
Reliability And Validity ◽  
Well Being ◽  
Computer Assisted ◽  
Emotional States ◽  
Self Reports ◽  
Health Related ◽  
Lower Variability

Abstract. Most research in health psychology is based on retrospective self reports, which are distorted by recall biases and have low ecological validity. To overcome such limitations we developed computer assisted diary approaches to assess health related behaviours in individuals’, couples’ and families’ daily life. The event- and time-sampling-based instruments serve to assess appraisals of the current situation, feelings of physical discomfort, current emotional states, conflict and emotion regulation in daily life. They have proved sufficient reliability and validity in the context of individual, couple and family research with respect to issues like emotion regulation and health. As examples: Regarding symptom reporting curvilinear pattern of frequencies over the day could be identified by parents and adolescents; or psychological well-being is associated with lower variability in basic affect dimensions. In addition, we report on preventive studies to improve parental skills and enhance their empathic competences towards their baby, and towards their partner.

Beliefs about emotion shift dynamically alongside momentary affect

2019 ◽  
Author(s):  
Jennifer Veilleux ◽  
Elise Warner ◽  
Danielle Baker ◽  
Kaitlyn Chamberlain
Keyword(s):  
Self Efficacy ◽  
Daily Life ◽  
Borderline Personality ◽  
Personality Pathology ◽  
Emotional States ◽  
Assessment Study ◽  
Directed Action ◽  
Emotion Beliefs ◽  
Ecological Momentary ◽  
Momentary Assessment

This study examined if beliefs about emotion change across emotional contexts in daily life, and investigated whether people with prominent features of borderline personality pathology experience greater shifts in emotion beliefs during emotional states compared to people without borderline features. Undergraduate participants with (n = 49) and without borderline features (n = 50) completed a one week ecological momentary assessment study where 7x/day they provided ratings of affect, nine different beliefs about emotion and indicators of momentary self-efficacy. Results indicated a significant between-person element to emotion beliefs, supporting the notion of beliefs as relatively schematic. In addition, people with borderline features generally experienced greater instability of beliefs over time compared to people without borderline features. In addition, most of the beliefs about emotion shifted with either positive or negative affect. For many of the emotion beliefs, the relationships between affect and belief were moderated by borderline group. Finally, momentary beliefs about emotion also predicted momentary self-efficacy for tolerating distress and exerting willpower. Taken together, results confirm that beliefs about emotion can fluctuate in daily life and that there are implications for emotion beliefs for people who struggle with emotion regulation and impulsivity (i.e., people with features of borderline personality) as well as for self-efficacy in tolerating emotion and engaging in goal-directed action.

Modern prevention and active longevity programs on the basis of disruptive domestic technologies: positive experience and prospects for application

2020 ◽  
pp. 66-73
Author(s):  
A. Simonova ◽  
S. Chudakov ◽  
R. Gorenkov ◽  
V. Egorov ◽  
A. Gostry ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Early Detection ◽  
Laboratory Diagnostics ◽  
Positive Experience ◽  
Practical Application ◽  
Wide Range ◽  
Integrated Program ◽  
Long Term Experience ◽  
Early Detection And Prevention

The article summarizes the long-term experience of practical application of domestic breakthrough technologies of preventive personalized medicine for laboratory diagnostics of a wide range of socially significant non-infectious diseases. Conceptual approaches to the formation of an integrated program for early detection and prevention of civilization diseases based on these technologies are given. A vision of the prospects for the development of this area in domestic and foreign medicine has been formed.

scholarly journals Promoting Generalized Learning in Balance Recovery Interventions

2021 ◽  
Vol 11 (3) ◽  
pp. 402
Author(s):  
Sara A. Harper ◽  
Anne Z. Beethe ◽  
Christopher J. Dakin ◽  
David A. E. Bolton
Keyword(s):  
Older Adults ◽  
Motor Learning ◽  
Daily Life ◽  
Balance Training ◽  
Community Dwelling ◽  
Specific Training ◽  
Balance Recovery ◽  
Parallel Streams ◽  
Postural Perturbations ◽  
Community Dwelling Older Adults

Recent studies have shown balance recovery can be enhanced via task-specific training, referred to as perturbation-based balance training (PBT). These interventions rely on principles of motor learning where repeated exposure to task-relevant postural perturbations results in more effective compensatory balance responses. Evidence indicates that compensatory responses trained using PBT can be retained for many months and can lead to a reduction in falls in community-dwelling older adults. A notable shortcoming with PBT is that it does not transfer well to similar but contextually different scenarios (e.g., falling sideways versus a forward trip). Given that it is not feasible to train all conditions in which someone could fall, this limited transfer presents a conundrum; namely, how do we best use PBT to appropriately equip people to deal with the enormous variety of fall-inducing scenarios encountered in daily life? In this perspective article, we draw from fields of research that explore how general learning can be promoted. From this, we propose a series of methods, gleaned from parallel streams of research, to inform and hopefully optimize this emerging field where people receive training to specifically improve their balance reactions.

scholarly journals Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson’s Disease patients

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Robbin Romijnders ◽  
Elke Warmerdam ◽  
Clint Hansen ◽  
Julius Welzel ◽  
Gerhard Schmidt ◽  
...  
Keyword(s):  
Older Adults ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Daily Life ◽  
Neurological Diseases ◽  
Detection Performance ◽  
Measurement Unit ◽  
Straight Line ◽  
Optical Motion ◽  
Task Conditions

Abstract Background Identification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson’s disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions. Methods Participants (older adults, people with Parkinson’s disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories. Results The detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall $$=$$ = 100%, precision $$=$$ = 100%, F1 score $$=$$ = 100%; FC: recall $$=$$ = 100%, precision $$=$$ = 100%, F1 score $$=$$ = 100%), slalom walking (IC: recall $$=$$ = 100%, precision $$\ge$$ ≥ 99%, F1 score $$=$$ = 100%; FC: recall $$=$$ = 100%, precision $$\ge$$ ≥ 99%, F1 score $$=$$ = 100%), and turning (IC: recall $$\ge$$ ≥ 85%, precision $$\ge$$ ≥ 95%, F1 score $$\ge$$ ≥ 91%; FC: recall $$\ge$$ ≥ 84%, precision $$\ge$$ ≥ 95%, F1 score $$\ge$$ ≥ 89%). Conclusions Shank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.

scholarly journals Early Detection of Freezing of Gait during Walking Using Inertial Measurement Unit and Plantar Pressure Distribution Data

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2246
Author(s):  
Scott Pardoel ◽  
Gaurav Shalin ◽  
Julie Nantel ◽  
Edward D. Lemaire ◽  
Jonathan Kofman
Keyword(s):  
Early Detection ◽  
Plantar Pressure ◽  
Inertial Measurement Unit ◽  
Binary Classification ◽  
Freezing Of Gait ◽  
Pressure Sensors ◽  
Measurement Unit ◽  
Distribution Data ◽  
Inertial Measurement ◽  
Plantar Pressure Distribution

Freezing of gait (FOG) is a sudden and highly disruptive gait dysfunction that appears in mid to late-stage Parkinson’s disease (PD) and can lead to falling and injury. A system that predicts freezing before it occurs or detects freezing immediately after onset would generate an opportunity for FOG prevention or mitigation and thus enhance safe mobility and quality of life. This research used accelerometer, gyroscope, and plantar pressure sensors to extract 861 features from walking data collected from 11 people with FOG. Minimum-redundancy maximum-relevance and Relief-F feature selection were performed prior to training boosted ensembles of decision trees. The binary classification models identified Total-FOG or No FOG states, wherein the Total-FOG class included data windows from 2 s before the FOG onset until the end of the FOG episode. Three feature sets were compared: plantar pressure, inertial measurement unit (IMU), and both plantar pressure and IMU features. The plantar-pressure-only model had the greatest sensitivity and the IMU-only model had the greatest specificity. The best overall model used the combination of plantar pressure and IMU features, achieving 76.4% sensitivity and 86.2% specificity. Next, the Total-FOG class components were evaluated individually (i.e., Pre-FOG windows, Freeze windows, transition windows between Pre-FOG and Freeze). The best model detected windows that contained both Pre-FOG and FOG data with 85.2% sensitivity, which is equivalent to detecting FOG less than 1 s after the freeze began. Windows of FOG data were detected with 93.4% sensitivity. The IMU and plantar pressure feature-based model slightly outperformed models that used data from a single sensor type. The model achieved early detection by identifying the transition from Pre-FOG to FOG while maintaining excellent FOG detection performance (93.4% sensitivity). Therefore, if used as part of an intelligent, real-time FOG identification and cueing system, even if the Pre-FOG state were missed, the model would perform well as a freeze detection and cueing system that could improve the mobility and independence of people with PD during their daily activities.

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