Application of cognitive rehabilitation theory to the development of smart prompting technologies

Effects of computer-based cognitive training vs. paper-and-pencil-based training on the cognitive development of typically developing children: Protocol for a randomized controlled trial

The research aims to evaluate the effectiveness of a computerized cognitive training program in improving executive functions and attention in elementary school children, compared to a traditional paper-and-pencil intervention. The study has been formulated as a randomized controlled trial with pre- and post-intervention measures. For the study, third-grade children with typical development aged between 7 and 9 years will be recruited. Participants will be randomly assigned to the two study arms (control and experimental). The experimental group will participate in a computerized intervention using the NeuronUp cognitive stimulation platform for 8 weeks, twice a week. Sessions will be conducted using computers in the computer lab of the participating educational institution. The active control group will engage in paper-and-pencil cognitive training for the same duration and intensity as the experimental group. Evaluators will be blinded to the assignment, and participants will be blinded to the target intervention. Hypothesis testing will be conducted through ANOVA-MR, and logistic regressions will be implemented to assess the effect of socioeconomic variables on children's performance. These results are expected to contribute to the discussion on the opportunities and benefits offered by cognitive training programs on the cognitive development of typically developing children.

A systematic review of reminder and guidance systems for Alzheimer's Disease and Related Dementias patients: context, barriers and facilitators

PURPOSE

To present the latest available research assessing the actual impact of reminder and guidance technologies for daily activities in Alzheimer's Disease and Related Dementia's patients, outlining design implications for these technologies.

MATERIALS AND METHODS

The search was conducted in the ACM Digital Library, IEEExplore, ScienceDirect, PubMed, Cochrane Library, Sage Journal, ResearchGate, and SemanticScholar. An iteratively-developed Boolean search string was built including up to 18 AND/OR terms across Four categories (Memory Aids, Technology, Daily Activities, Memory Impairment). We qualitatively analyzed the findings and discussions of the findings reported in 40 studies in our corpus to determine common barriers to, and facilitators of, effective intervention implementation and adoption.

RESULTS

Forty studies fulfilled the inclusion and exclusion criteria. In existing studies, individuals with Alzheimer's Disease and Related Dementias understand the usefulness of different functions that can be provided within an app to assist with everyday tasks. There was a high level of heterogeneity regarding the studies' location, duration, and evaluation methodology.

CONCLUSIONS

There is a need for assistive reminder and guidance technologies to be tailored towards autonomy, identity and personalization. Future work should include motivating features to aid during mood changes and feelings of insecurity.

COOK technology to support meal preparation following a severe traumatic brain injury: a usability mixed-methods single-case study in a real-world environment

INTRODUCTION

Following a traumatic brain injury (TBI), meal preparation may become challenging as it involves multiple cognitive abilities and sub-tasks. To support this population, the Cognitive Orthosis for coOKing (COOK) was developed in partnership with an alternative residential resource for people with severe TBI. However, little is known about the usability of this technology to support people with TBI living in their own homes.

METHODS

A usability study was conducted using a mixed-methods single-case design with a 35-year-old man with severe TBI living alone at home. The number of assistances provided, time taken and the percentage of unnecessary actions during a meal preparation task were documented nine times to explore the usability of COOK. Interviews were also conducted with the participant to document his satisfaction with COOK. Potential benefits were explored via the number of meals prepared per week.

RESULTS

The usability of COOK was shown to be promising as the technology helped the participant prepare complex meals, while also reducing the number of assistances needed and the percentage of unnecessary actions. However, several technical issues and contextual factors influenced the efficiency and the participant's satisfaction with COOK. Despite improving his self-confidence, COOK did not help the participant prepare more meals over time.

CONCLUSION

This study showed that COOK was easy to use and promising, despite technical and configuration issues. Results suggest the importance of further technological developments to improve COOK's usability and fit with the needs of people with TBI living in their own homes.

Cognitive assistance to support individuals with traumatic brain injury using a minimal and personalised approach: A conversion mixed methods study using video analysis

INTRODUCTION

Individuals with traumatic brain injury (TBI) frequently need assistance to manage complex everyday activities. However, little is known about the types of cognitive assistance that can be used to facilitate optimal independence. A conversion mixed method study using video analysis was conducted to describe assistance provided by trained occupational therapists during three everyday tasks carried out in the participants' homes and surrounding environments.

METHODS

Forty-five people with moderate and severe TBI were tested by three occupational therapists using the Instrumental Activities of Daily Living Profile, an observation-based assessment that documents independence in complex everyday activities and the minimal assistance required to attain task goals. Using video analysis, difficulties experienced by the people with TBI during a meal preparation and grocery shopping task, and the cognitive assistance provided by the occupational therapists in response to these difficulties, were documented. Statistical analyses were also completed to identify the main difficulties and types of cognitive assistance provided during the evaluation, for the whole group and depending on their level of independence.

RESULTS

Nine types of cognitive assistance were used by occupational therapists, including implicit (stimulating thought processes), and more explicit assistance (cueing), to facilitate task performance. When needed, motivational assistance, which consisted of encouraging participants to think for themselves, was also used. Stimulating thought processes was mostly used to support goal formulation and planning, whereas cueing was used in numerous instances. Participants with lower levels of independence received more assistance of almost all types to support them.

CONCLUSION

Using these findings, training could be developed for caregivers and occupational therapists to support them in providing minimal and personalised cognitive assistance. Further research is needed to examine the extent to which all types of cognitive assistance are effective in helping various cognitive profiles of people with TBI attain optimal independence.

Virtual Reality Technology as an Educational and Intervention Tool for Children with Autism Spectrum Disorder: Current Perspectives and Future Directions

The worldwide rising trend of autism spectrum disorder (ASD) calls for innovative and efficacious techniques for assessment and treatment. Virtual reality (VR) technology gains theoretical support from rehabilitation and pedagogical theories and offers a variety of capabilities in educational and interventional contexts with affordable products. VR is attracting increasing attention in the medical and healthcare industry, as it provides fully interactive three-dimensional simulations of real-world settings and social situations, which are particularly suitable for cognitive and performance training, including social and interaction skills. This review article offers a summary of current perspectives and evidence-based VR applications for children with ASD, with a primary focus on social communication, including social functioning, emotion recognition, and speech and language. Technology- and design-related limitations, as well as disputes over the application of VR to autism research and therapy, are discussed, and future directions of this emerging field are highlighted with regards to application expansion and improvement, technology enhancement, linguistic diversity, and the development of theoretical models and brain-based research.

Remind Me To Remember: A pilot study of a novel smartphone reminder application for older adults with dementia and mild cognitive impairment

The SmartPrompt is a smartphone-based reminder application informed by a neuropsychological model of functional disability. This laboratory-based pilot study examined the SmartPrompt feasibility, efficacy, and subjective usability using a within-participant, counterbalanced, cross-over design. Ten participants (M age = 80.3 + 8.2; M education = 15.7 + 2.5; 60% female) with mild cognitive impairment or mild dementia completed the Remember to Drink Test, which required preparing a glass of water at four predetermined times, in a SmartPrompt (SP) and Unprompted condition (UP). Written cues and a clock were available in both conditions; however, in the SP, the smartphone presented auditory alarms and visual reminders to obtain the water at specified times and required photo logging. In a separate session, caregivers were trained and tested on configuring the SmartPrompt. Overall, caregivers and participants learned to effectively use the SmartPrompt. Caregivers achieved near-perfect scores on the configuration quiz and responded well to training. Participants completed significantly more Remember to Drink tasks in the SP (93%) than UP (56%); checking the cues/clock decreased by 87% in the SP. Usability ratings were excellent among caregivers and fair among participants. Results indicate that the SmartPrompt holds promise for reducing functional disability in older adults with cognitive difficulties in at-home contexts.

Smart Co-housing for People With Disabilities: A Preliminary Assessment of Caregivers' Interaction With the DOMHO System

Millions of people with motor and cognitive disabilities face hardships in daily life due to the limited accessibility and inclusiveness of living spaces which limit their autonomy and independence. The DOMHO project deals with these fundamental issues by leveraging an innovative solution: a smart co-housing apartment. Besides, the project aims at exploiting the well know effects of co-housing on individuals' health and well-being in combination with ambient assisted living technologies. The present study focused on the interaction of caregivers with the control application of an integrated smart system. Participants performed different tasks, fill out a questionnaire, and were interviewed. Performance and usability of the user interface, trust in technology, privacy, and attitudes towards home automation were explored. A series of guidelines for domotic technology control interfaces design was identified, and a high level of trust in these advanced tools was shown. Caregivers considered smart technologies as a work aid and a means for enhancing autonomy and life quality for users with disabilities.

The goal-control model: An integrated neuropsychological framework to explain impaired performance of everyday activities

OBJECTIVE

This review describes the relatively small body of neuropsychological and cognitive research conducted over the past 100 years focused on theoretical models explaining the neurocognitive processes that support everyday functioning and the breakdown of functional abilities in the face of neurological damage or disease.

METHOD

The historical roots of the theories of everyday activities based on direct observation of behavior in neurology and diary reports of everyday errors in cognitive psychology are presented, followed by a review of the empirical findings and resulting theoretical conceptualizations from case studies and group studies of various clinical populations in neuropsychology.

RESULTS

We conclude with a new framework (the goal-control model) that integrates the most recent empirical findings in neuropsychology with mechanisms proposed by cognitive models.

CONCLUSIONS

The goal-control model offers empirically supported solutions to understanding and predicting functioning in the real world. This new model generates testable predictions for future research and provides guidance for clinical assessment and interventions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

An overview of the digital solutions for helping people with aphasia through bibliometric analysis

This paper gives insights into recent research developments in the field of digital solutions for people with aphasia and tries to analyse its impact on their rehabilitation. A bibliometric research approach is used for data collection. Relevant studies were extracted from seven major academic databases from years 2000 to 2019 inclusive. The systematic process resulted in 986 studies. The average growth in this field is 4%, which is less compared to other research areas. However, the average citations per paper is 7.27, which represents a medium level of publication quality. Scopus and Web of Science are leading databases for the number of studies (379 and 264) and quality of publications (P-Index: 49.26 and 32.85), respectively. The USA, with 42% of publications, leads this research field, followed by the UK with 15%. Both countries have national aphasia strategies in place through charities (not government level strategies), which potentially contributed to their research leadership. The results show that recent advances in digital solutions have the potential to support people with aphasia. However, further work is needed at both academic and government levels to deliver more research contributions and funding for the rehabilitation of people with aphasia.

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The countries with clear national aphasia strategies in place lead this research field.

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Western countries carry most of the research for aphasia; the global view of this research area is still messing.

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Personal care, in combination with digital solutions, can yield better results.

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The fully immersive virtual reality solutions offer close to real-life interaction experience for the people with aphasia and their surroundings inside the virtual space.

A survey of research trends in assistive technologies using information modelling techniques

BACKGROUND

Despite the rapid proliferation and emphasis on technology, the use of assistive technology among individuals with varying disabilities and age is different. This situation instigates the need for a systematic review to gain a realistic understanding of prominent issues, research trends and assistive technology applications with minimal bias.

OBJECTIVE

Identification of leading researchers and prominent publications in assistive technologies. Subsequently, semantic relation between qualitative and quantitative research literature on assistive technologies was explored to future research directions.

METHODS

A manual search across reputed research databases was done to find out relevant literature from January 2005 to April 2020. In this paper, latent semantic analysis (LSA) was done to develop an information model for achieving defined objectives.

RESULTS

A corpus of 367 research papers published during 2005-2020 was processed using LSA. Term frequency, inverse document frequency of high loading terms provided five major topic solutions. Marcia Scherer, Rory Cooper and Stefano Federici are most noticed authors in assistive technology research. "Smart Assistive Technologies" and "Wearable Technologies for Rehabilitation" came out as contemporary research trends within assistive technologies.

CONCLUSIONS

The manuscript concludes the fact that assistive technologies for rehabilitation are experiencing a transition from standalone mechanical devices towards smart, wearable and connected devices.Implications for RehabilitationCustomized assistive devices could be programmed for multiple uses.User data privacy and internet dependency of smart assistive technologies must be taken care of while designing smart assistive devices for rehabilitation.Fog devices could eliminate the latency issues associated with cloud-based rehabilitation services.

Using a cognitive orthosis to support older adults during meal preparation: Clinicians' perspective on COOK technology

Introduction

Occupational therapists promote safety and autonomy of older adults with cognitive impairments. A technology, named COOK, offers support on a touch screen installed next to the stove to support task performance while correcting risky behaviors. We aimed to document (1) the functional profiles according the diagnosis (2) the types of interventions used to increase autonomy in the kitchen (3) the facilitators and obstacles to the implementation of COOK with this clientele.

Methods

Four focus groups were conducted with occupational therapists (n = 24) and were transcribed and analyzed using thematic analysis, including coding and matrix building.

Results

Occupational therapists identified different (1) functional profiles and (2) interventions for both diagnoses. The use of COOK (3) could be more beneficial in mild cognitive impairment, as many barriers occur for the use in Alzheimer's disease. Some parameters, such as digital control of the stove and complex information management, need to be simplified.

Discussion

According to occupational therapists, this technology is particularly applicable to people with mild cognitive impairment, because this population has better learning abilities.

Conclusion

This study documented the specific needs of older adults with cognitive impairments as well as interventions used by occupational therapists. The perspectives of caregivers should be captured in future research.

Using an interactive digital calendar with mobile phone reminders by senior people - a focus group study

Background

New technologies such as mobile/smartphones have the potential to help senior people perform everyday activities. However, senior people may find it difficult using mobile/smartphones, especially the digital calendar and short text message features. Therefore, senior people might need user-friendly, flexible, and interactive digital calendars that provide them with active reminders about their everyday activities. This study focuses on community dwelling seniors’ experiences learning and using RemindMe, an interactive digital calendar with active reminders, as part of customizing an intervention appropriate for senior people with cognitive impairments.

Methods

Four focus groups were conducted with 20 community dwelling seniors (11 men and 9 women) who all had used RemindMe for six weeks. The focus groups were tape recorded, transcribed verbatim, and analysed using content analysis.

Results

For participants in this study, using a calendar was an essential part of their everyday lives, but only a few had experiences using a digital calendar. Although the participants described RemindMe as easy to use, they had a difficult time incorporating RemindMe into their daily routines. In part, these difficulties were the result of the participants needing to change their mobile/smartphone routines. Some participants felt that using an interactive digital calendar was a sign of modernity allowing them to take part in the society at large, but others felt that their inability to use the technology was due to their age, dependence, and loss of function. Participants found that receiving active reminders through short text messages followed by actively acknowledging the reminder helped them perform more everyday life activities. This feature gave them a higher sense of independence and control.

Conclusions

Community dwelling seniors found that RemindMe was easy to learn and to use, although they also found it challenging to integrate into their everyday lives. For senior people to make the effort to develop new routines for mobile/smartphone use, a prerequisite for using a digital calendar, they need to be motivated and believe that the technology will make their lives better.

A nurse-driven method for developing artificial intelligence in "smart" homes for aging-in-place

OBJECTIVES

To offer practical guidance to nurse investigators interested in multidisciplinary research that includes assisting in the development of artificial intelligence (AI) algorithms for "smart" health management and aging-in-place.

METHODS

Ten health-assistive Smart Homes were deployed to chronically ill older adults from 2015 to 2018. Data were collected using five sensor types (infrared motion, contact, light, temperature, and humidity). Nurses used telehealth and home visitation to collect health data and provide ground truth annotation for training intelligent algorithms using raw sensor data containing health events.

FINDINGS

Nurses assisting with the development of health-assistive AI may encounter unique challenges and opportunities. We recommend: (a) using a practical and consistent method for collecting field data, (b) using nurse-driven measures for data analytics, (c) multidisciplinary communication occur on an engineering-preferred platform.

CONCLUSIONS

Practical frameworks to guide nurse investigators integrating clinical data with sensor data for training machine learning algorithms may build capacity for nurses to make significant contributions to developing AI for health-assistive Smart Homes.

Prompting Technology and Persons With Dementia: The Significance of Context and Communication

Background and Objectives

Smart home auto-prompting has the potential to increase the functional independence of persons with dementia (PWDs) and decrease caregiver burden as instrumental activities of daily living (IADLs) are completed at home. To improve prompting technologies, we sought to inductively understand how PWDs responded to auto-prompting while performing IADL tasks.

Research Design and Methods

Fifteen PWDs completed eight IADLs in a smart home testbed and received a hierarchy of verbal auto-prompts (indirect, direct, multimodal) as needed for task completion. Two researchers viewed archived videos and recorded the observed behaviors of the PWDs and their reflections watching the PWDs. Using qualitative descriptive methods, an interdisciplinary analytic team reviewed transcripts and organized data into themes using content analysis.

Results

Context and Communication emerged as the major themes, suggesting that positive user experiences will require auto-prompting systems to account for a multitude of contextual factors (individual and environmental) such as level of cognitive impairment, previous exposure to task, and familiarity of environment. Communicating with another human rather than an automated prompting system may be important if individuals begin to exhibit signs of stress while completing activities.

Discussion and Implications

Additional work is needed to create auto-prompting systems that provide specific, personalized, and flexible prompts. Holistic conceptualization of "successful task completion" is needed and a positive end-user experience will be key to utility. Such systems will benefit from including positive reinforcement, training, and exploration of how, and whether, direct human involvement can be minimized during the provision of in-home care.

Impact evaluation of assistive technology support for the people with dementia

This study explores important factors of assistive technology (AT) and evaluates their relative impact on AT effectiveness and retention. Questionnaire based survey is used for data collection from 327 people with dementia (PWD). This empirical study uses statistical techniques including exploratory factor analysis for factor identification, linear regression for impact study, Kruskal Wallis H and Mann Whitney U tests for the statistical significant study in terms of demographic and characteristics. The exploratory factor analysis results into 11 factors: operational support, physical support, psychological support, social support, cultural match, reduced external help, affordability, travel help, compatibility, effectiveness and retention. The results reveal that social support, psychological support and travel help and reduced external help strongly impact on AT effectiveness and retention. The users are motivated by socialization support through using AT without any external help. The use of AT during travelling improves confidence of the PWD and helps them psychologically.

A Low-Power Wearable Stand-Alone Tongue Drive System for People With Severe Disabilities

This paper presents a low-power stand-alone tongue drive system (sTDS) used for individuals with severe disabilities to potentially control their environment such as computer, smartphone, and wheelchair using their voluntary tongue movements. A low-power local processor is proposed, which can perform signal processing to convert raw magnetic sensor signals to user-defined commands, on the sTDS wearable headset, rather than sending all raw data out to a PC or smartphone. The proposed sTDS significantly reduces the transmitter power consumption and subsequently increases the battery life. Assuming the sTDS user issues one command every 20 ms, the proposed local processor reduces the data volume that needs to be wirelessly transmitted by a factor of 64, from 9.6 to 0.15 kb/s. The proposed processor consists of three main blocks: serial peripheral interface bus for receiving raw data from magnetic sensors, external magnetic interference attenuation to attenuate external magnetic field from the raw magnetic signal, and a machine learning classifier for command detection. A proof-of-concept prototype sTDS has been implemented with a low-power IGLOO-nano field programmable gate array (FPGA), bluetooth low energy, battery and magnetic sensors on a headset, and tested. At clock frequency of 20 MHz, the processor takes 6.6 s and consumes 27 nJ for detecting a command with a detection accuracy of 96.9%. To further reduce power consumption, an application-specified integrated circuit processor for the sTDS is implemented at the postlayout level in 65-nm CMOS technology with 1-V power supply, and it consumes 0.43 mW, which is 10 lower than FPGA power consumption and occupies an area of only 0.016 mm.

Learning Activity Predictors from Sensor Data: Algorithms, Evaluation, and Applications

Recent progress in Internet of Things (IoT) platforms has allowed us to collect large amounts of sensing data. However, there are significant challenges in converting this large-scale sensing data into decisions for real-world applications. Motivated by applications like health monitoring and intervention and home automation we consider a novel problem called Activity Prediction, where the goal is to predict future activity occurrence times from sensor data. In this paper, we make three main contributions. First, we formulate and solve the activity prediction problem in the framework of imitation learning and reduce it to a simple regression learning problem. This approach allows us to leverage powerful regression learners that can reason about the relational structure of the problem with negligible computational overhead. Second, we present several metrics to evaluate activity predictors in the context of real-world applications. Third, we evaluate our approach using real sensor data collected from 24 smart home testbeds. We also embed the learned predictor into a mobile-device-based activity prompter and evaluate the app for 9 participants living in smart homes. Our results indicate that our activity predictor performs better than the baseline methods, and offers a simple approach for predicting activities from sensor data.

Using Smartphones to Help People with Intellectual and Sensory Disabilities Perform Daily Activities

Background

People with mild-to-moderate intellectual disability and sensory impairments often fail to take initiative in starting and carrying out daily activities, with negative consequences for their occupational condition and social status. Their failure seems due to their inability to determine the right time for the activities and to remember all the activity steps.

Aim

This study assessed a smartphone intervention, which was designed to help eight participants (four presenting with intellectual disability and blindness and four presenting with intellectual disability and hearing impairment) to independently start and carry out daily activities at appropriate times.

Method

The intervention was introduced according to a non-concurrent multiple baseline design across participants. During the intervention, each participant was provided with a smartphone, which was fitted with the time schedule of his or her activities and the verbal or pictorial instructions for the single steps of those activities. When the time for an activity was reached, the participant was automatically reminded to start that activity and, thereafter, he or she was presented with the instructions for it.

Results

The use of the smartphone intervention promoted great improvement over the baseline for all participants. That is, the participants managed to (a) independently start the activities at the scheduled times and (b) carry out those activities with high levels of accuracy.

Conclusion

A smartphone intervention, such as that used in this study, may help people with mild-to-moderate intellectual disability and sensory impairments to successfully engage in daily activities.

Toward personalized and context-aware prompting for smartphone-based intervention

Intervention strategies can help individuals with cognitive impairment to increase adherence to instructions, independence, and activity engagement and reduce errors on everyday instrumental activities of daily living (IADLs) and caregiver burden. However, to be effective, intervention prompts should be given at a time that does not interrupt other important user activities and is more convenient. In this paper, we propose an intelligent personalized intervention system for smartphones. In our approach, we use context and activity awareness to time prompts when they will most likely be viewed and used. Our result based on real data collected using smartphone motion sensors demonstrate that the proposed approach can detect the time-frame of a user response with an average accuracy of 65% and reduce the inefficiency by 39%, on average, compared to different static time interventions which shows the possibilities and advantages of the proposed system to increase user satisfaction and response rate.

One-Class Classification-Based Real-Time Activity Error Detection in Smart Homes

Caring for individuals with dementia is frequently associated with extreme physical and emotional stress, which often leads to depression. Smart home technology and advances in machine learning techniques can provide innovative solutions to reduce caregiver burden. One key service that caregivers provide is prompting individuals with memory limitations to initiate and complete daily activities. We hypothesize that sensor technologies combined with machine learning techniques can automate the process of providing reminder-based interventions. The first step towards automated interventions is to detect when an individual faces difficulty with activities. We propose machine learning approaches based on one-class classification that learn normal activity patterns. When we apply these classifiers to activity patterns that were not seen before, the classifiers are able to detect activity errors, which represent potential prompt situations. We validate our approaches on smart home sensor data obtained from older adult participants, some of whom faced difficulties performing routine activities and thus committed errors.

Subjective cognitive complaints and objective memory performance influence prompt preference for instrumental activities of daily living

INTRODUCTION

Declines in memory and executive functioning often lead to difficulties completing instrumental activities of daily living (IADLs). Prompting technologies have the potential to help promote aging in place by providing support for the initiation and accurate completion of IADLs. In this study, we evaluate preferences of older adults for different levels of prompting support based on subjective and objective measures of cognitive functioning.

METHOD

Participants were 170 community-dwelling older adults split into two cognitive complaint groups: cognitive complaints and few cognitive complaints. After completing six IADL tasks (e.g., organize a pillbox, cook), each participant was asked to make a specific error (e.g., leave stove on) on three of the tasks. They were then prompted to correct the error with one of three different prompt modes: verbal indirect, verbal direct, multimodal verbal direct and video.

RESULTS

The cognitive complaints group reported greater preference for the multimodal prompt compared to the few cognitive complaints group. The indirect prompt was the least preferred by both groups. Furthermore, participants who recalled less on objective memory measures preferred more support in terms of prompt mode. Executive functioning did not appear to be related to prompt preference.

CONCLUSION

Level of subjective cognitive complaints and objective memory performance may influence amount of support preferred in a prompt.

Automated Detection of Activity Transitions for Prompting

Individuals with cognitive impairment can benefit from intervention strategies like recording important information in a memory notebook. However, training individuals to use the notebook on a regular basis requires a constant delivery of reminders. In this work, we design and evaluate machine learning-based methods for providing automated reminders using a digital memory notebook interface. Specifically, we identify transition periods between activities as times to issue prompts. We consider the problem of detecting activity transitions using supervised and unsupervised machine learning techniques, and find that both techniques show promising results for detecting transition periods. We test the techniques in a scripted setting with 15 individuals. Motion sensors data is recorded and annotated as participants perform a fixed set of activities. We also test the techniques in an unscripted setting with 8 individuals. Motion sensor data is recorded as participants go about their normal daily routine. In both the scripted and unscripted settings a true positive rate of greater than 80% can be achieved while maintaining a false positive rate of less than 15%. On average, this leads to transitions being detected within 1 minute of a true transition for the scripted data and within 2 minutes of a true transition on the unscripted data.

Using virtual reality for cognitive training of the elderly

There is a pressing demand for improving the quality and efficacy of health care and social support services needed by the world's growing elderly population, especially by those affected by mild cognitive impairment (MCI) and Alzheimer's disease (AD)-type early-stage dementia. Meeting that demand can significantly benefit from the deployment of innovative, computer-based applications capable of addressing specific needs, particularly in the area of cognitive impairment mitigation and rehabilitation. In that context, we present here our perspective viewpoint on the use of virtual reality (VR) tools for cognitive rehabilitation training, intended to assist medical personnel, health care workers, and other caregivers in improving the quality of daily life activities of people with MCI and AD. We discuss some effective design criteria and developmental strategies and suggest some possibly useful protocols and procedures. The particular innovative supportive advantages offered by the immersive interactive characteristics inherent to VR technology are discussed.

Prompting technologies: A comparison of time-based and context-aware transition-based prompting

BACKGROUND

While advancements in technology have encouraged the development of novel prompting systems to support cognitive interventions, little research has evaluated the best time to deliver prompts, which may impact the effectiveness of these interventions.

OBJECTIVE

This study examined whether transition-based context prompting (prompting an individual during task transitions) is more effective than traditional fixed time-based prompting.

METHODS

Participants were 42 healthy adults who completed 12 different everyday activities, each lasting 1-7 minutes, in an experimental smart home testbed and received prompts to record the completed activities from an electronic memory notebook. Half of the participants were delivered prompts during activity transitions, while the other half received prompts every 5 minutes. Participants also completed Likert-scale ratings regarding their perceptions of the prompting system.

RESULTS

Results revealed that participants in the transition-based context prompting condition responded to the first prompt more frequently and rated the system as more convenient, natural, and appropriate compared to participants in the time-based condition.

CONCLUSIONS

Our findings suggest that prompting during activity transitions produces higher adherence to the first prompt and more positive perceptions of the prompting system. This is an important finding given the benefits of prompting technology and the possibility of improving cognitive interventions by using context-aware transition prompting.

RACOG and wRACOG: Two Probabilistic Oversampling Techniques

As machine learning techniques mature and are used to tackle complex scientific problems, challenges arise such as the imbalanced class distribution problem, where one of the target class labels is under-represented in comparison with other classes. Existing oversampling approaches for addressing this problem typically do not consider the probability distribution of the minority class while synthetically generating new samples. As a result, the minority class is not well represented which leads to high misclassification error. We introduce two Gibbs sampling-based oversampling approaches, namely RACOG and wRACOG, to synthetically generating and strategically selecting new minority class samples. The Gibbs sampler uses the joint probability distribution of attributes of the data to generate new minority class samples in the form of Markov chain. While RACOG selects samples from the Markov chain based on a predefined lag, wRACOG selects those samples that have the highest probability of being misclassified by the existing learning model. We validate our approach using five UCI datasets that were carefully modified to exhibit class imbalance and one new application domain dataset with inherent extreme class imbalance. In addition, we compare the classification performance of the proposed methods with three other existing resampling techniques.

Automatic Task Assistance for People with Cognitive Disabilities in Brushing Teeth - A User Study with the TEBRA System

People with cognitive disabilities such as dementia and intellectual disabilities tend to have problems in coordinating steps in the execution of Activities of Daily Living (ADLs) due to limited capabilities in cognitive functioning. To successfully perform ADLs, these people are reliant on the assistance of human caregivers. This leads to a decrease of independence for care recipients and imposes a high burden on caregivers. Assistive Technology for Cognition (ATC) aims to compensate for decreased cognitive functions. ATC systems provide automatic assistance in task execution by delivering appropriate prompts which enable the user to perform ADLs without any assistance of a human caregiver. This leads to an increase of the user’s independence and to a relief of caregiver’s burden. In this article, we describe the design, development and evaluation of a novel ATC system. The TEBRA (TEeth BRushing Assistance) system supports people with moderate cognitive disabilities in the execution of brushing teeth. A main requirement for the acceptance of ATC systems is context awareness: explicit feedback from the user is not necessary to provide appropriate assistance. Furthermore, an ATC system needs to handle spatial and temporal variance in the execution of behaviors such as different movement characteristics and different velocities. The TEBRA system handles spatial variance in a behavior recognition component based on a Bayesian network classifier. A dynamic timing model deals with temporal variance by adapting to different velocities of users during a trial. We evaluate a fully functioning prototype of the TEBRA system in a study with people with cognitive disabilities. The main aim of the study is to analyze the technical performance of the system and the user’s behavior in the interaction with the system with regard to the main hypothesis: is the TEBRA system able to increase the user’s independence in the execution of brushing teeth?

Applications of technology in neuropsychological assessment

Most neuropsychological assessments include at least one measure that is administered, scored, or interpreted by computers or other technologies. Despite supportive findings for these technology-based assessments, there is resistance in the field of neuropsychology to adopt additional measures that incorporate technology components. This literature review addresses the research findings of technology-based neuropsychological assessments, including computer- and virtual reality-based measures of cognitive and functional abilities. We evaluate the strengths and limitations of each approach, and examine the utility of technology-based assessments to obtain supplemental cognitive and behavioral information that may be otherwise undetected by traditional paper-and-pencil measures. We argue that the potential of technology use in neuropsychological assessment has not yet been realized, and continued adoption of new technologies could result in more comprehensive assessment of cognitive dysfunction and in turn, better informed diagnosis and treatments. Recommendations for future research are also provided.

Naturalistic assessment of everyday activities and prompting technologies in mild cognitive impairment

Older adults with mild cognitive impairment (MCI) often have difficulty performing complex instrumental activities of daily living (IADLs), which are critical to independent living. In this study, amnestic multi-domain MCI (N = 29), amnestic single-domain MCI (N = 18), and healthy older participants (N = 47) completed eight scripted IADLs (e.g., cook oatmeal on the stove) in a smart apartment testbed. We developed and experimented with a graded hierarchy of technology-based prompts to investigate both the amount of prompting and type of prompts required to assist individuals with MCI in completing the activities. When task errors occurred, progressive levels of assistance were provided, starting with the lowest level needed to adjust performance. Results showed that the multi-domain MCI group made more errors and required more prompts than the single-domain MCI and healthy older adult groups. Similar to the other two groups, the multi-domain MCI group responded well to the indirect prompts and did not need a higher level of prompting to get back on track successfully with the tasks. Need for prompting assistance was best predicted by verbal memory abilities in multi-domain amnestic MCI. Participants across groups indicated that they perceived the prompting technology to be very helpful.