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Advisory Council January 2019 Meeting Presentation: Technology to Advance Assessment

Monday, January 28, 2019

Printer Friendly Version in PDF Format (18 PDF pages)


Technology to Advance Assessment & Interventions for Dementia

Jeffrey Kaye
Layton Professor of Neurology & Biomedical Engineering
ORCATECH - Oregon Center for Aging & Technology
NIA - Layton Aging & Alzheimer's Disease Center;

Contemporary Assessment

"How long have you been here? She seems to be trying to remember. Three weeks. What is this? I show her a pencil. A pen. A purse, key, diary and cigar are identified correctly. ... When objects are shown to her, she does not remember after a short time which objects have been shown..."
--- A. Alzheimer, Nov. 6, 1901

Still crazy after all these years...

Photos of the way treatment is handled.

Detecting Meaningful Change

Scatter chart. Line chart.
High variability in cognitive tests
-- ADNI Memory Composite Dodge et. al., 2014
High variability in self-report measures
-- UCLA Loneliness Scale
Austin et al., 2016

The way it should be...

Photos of the way treatment should be handled.

Pervasive Computing Technologies

  • Transform the ability to detect meaningful change
  • Increase the speed or efficiency of clinical trials and dementia research in general
  • Provide new fundamental insights into human biology and behavior

Transform the ability to detect meaningful change

Brain waves.

Challenges to developing new therapies

Study timeline.

Increase the speed or efficiency of clinical trials and dementia research in general

MCI Prevention Trial -- Sample Size Estimates
  Current Method Continuous Measures
  LM Delayed Recall* Computer Use** Walking Speed**
Dodge, et al., PLoS One, 2015
  • Reduces required sample size and/or time to identify meaningful change.
  • Reduces exposure to harm (fewer needed/ fewer exposed)
  • More precise estimates of the trajectory of change; allows for intra-individual predictions.
  • Provides the opportunity to substantially improve efficiency and inform go/no-go decisions of trials.

Provide new insights into human biology and behavior

Rhythm chart.
Disrupted Infradian Rhythms in MCI
Reynolds, et al., 2017

How? NIA - Technology Agnostic R & D Platform ORCATECH Life Laboratory + CART

Floor plan.
Kaye et al. J of Gerontol, 2011; Lyons et al. Frontiers in Aging Neurosci, 2015; Kaye et al. J of Visualized Experiments, 2018

ORCATECH - CART End-to-End System


CART - Collaborative Aging Research Using Technology

  • Established to address needed research capability for evidence building (facilitated by technology) in aging research.
  • Goal: Design and implement a scalable, disseminated technology system ('platform') for more effective aging research, ultimately deployable to 10,000+ homes
  • Focus on diversity, technology agnosticism, "future-proofing", use case flexibility, sustainability, facilitating secure data sharing.
  • Interagency U2C (U2CAG054397) with NIH (NIA, NIBIB, NCI, NINDS, NINR, NCATS, OBSSR,) and VA
  • Research Team: PI, Jeffrey Kaye, ORCATECH/Oregon Health & Science University; Nina Silverberg, NIA; Collaborators: Intel, U. Miami, Cornell, Rush, OSU, U. Penn, VA VISN 20

CART + ORCATECH Sites/Homes in U.S. and Canada

State map.

Assessments - Examples

Cartoon explaining how a toilet works.

Developing PD and Tx Response

Scatter graphs: Healthy, Diagnosed with Parkinson's Disease, Treatment with Sinement.

Physical Activity and Mobility Behaviors

Room activity distributions differentiating MCI vs not MCI
Room Bedroom Bathroom Kitchen Living Room Combined
F0.5 Score* 0.842 0.829 0.813 0.826 0.856
*F0.5 Scores window size w = 20 weeks; slide size = 4 weeks (with leave-one-subject-out cross validation)
  Trajectories of gait speed over time
Floor plan. Line chart.
Akl et al. Journal of Ambient Intelligence and Smart Environments, 2015 Dodge, et al. Neurology, 2012

Chronobiological Behavior

No Differences Between Groups in Self-Report Measures
Self-Report Measure Intact aMCI naMCI P value
Subjective Daytime Sleepiness 1.8 ± 0.2 1.5 ± 0.3 2.0 ± 0.3 0.69
Subjective Insomnia 1.3 ± 0.2 0.8 ± 0.3 1.6 ± 0.3 0.21
Subjective Restlessness 1.0 ± 0.1 0.4 ± 0.3 0.7 ± 0.2 0.34
Times up at night 1.1 ± 0.1 1.0 ± 0.3 1.0 ± 0.2 0.77
Scatter chart. Scatter chart.
Hayes, et al. Alzheimer Dis Assoc Disord. 2014
Hayes, et al. IEEE Eng Med Biol Soc, 2010

Cognition, Behavior, Motor Function: Computer Use

Self-Report screenshots. Scatter chart.
Kaye, et al. Alzheimers Dement. 2014; Silbert et al., Alzheimers Dement, 2015; Seelye et al. Alzheimers Dement.: Diagnosis, Assessment & Disease Monitoring, 2015; Seelye et al. Alzheimer's Disease & Assoc. Disorders, 2015; Seelye et al., Alzheimer & Dementia, 2018  
Table 4. Associations between cognitive status and mouse movement variability derived from one week of data
Covariate Outcome, movement curvature (IQR_K) Outcome, time spent idling (IQR_Idle)
Coefficient P value Coefficient P value
MCI (reference: cognitively intact group) 0.013 .008** 386.8 .04*
Age (y) -0.001 .03* -15.0 .31
Education (y) 0.002 .05 -12.4| .70
Abbreviations: IQR, interquartile range; MCI, mild cognitive impairment.
NOTE: *P <.05, **P <.01.

Digital biomarkers and Braak Score

  Brain sections.
Bar chart: None or I/II 171; III/IV 102; V/VI 33. Bar chart: None or I/II 71; III/IV 58; V/VI 50.
Bar chart: None or I/II 7.6; III/IV 8.3; V/VI 8.9. Bar chart: None or I/II 4; III/IV 5; V/VI 3.3.

Digital biomarkers and Plaque Score

Bar chart: None 144, Sparse 90, Moderate 56. Bar chart: None 65, Sparse 59, Moderate 47.
Bar chart: None 7.8, Sparse 8.4, Moderate 9.1. Bar chart: None 4.9, Sparse 5, Moderate 3.

Digital functional activity composite relative to plaque score

Digital Composite = Mobility + Cognition + Sleep + Socialization

Technologies advancing dementia intervention research - Examples

Photo of medicine bottles, beside a cartoon for the self-operating napkin.

Ambient Independence Measures (AIMS) for Guiding Care Transitions (R01AG042191)

  • During the three years of study -- low staff engagement:
    • 11/26 consented staff members logged in at least once to the activity dashboard.
    • Staff "page views", that is, number of pages of data looked at, ranged from 4-211 over the duration of data collection.
    • Mean seconds spent on a particular page view was 36 (range, 1-750)
    • Across 5 monthly email surveys, response rate of 31% (23/73).

Ambient Independence Measures Guiding Care Transitions

  • Bottom Line:
    • Technology worked well with unique metrics acting both as assessment and intervention
    • Inconclusive results -- despite high engagement and enthusiasm at entry and booster sessions, inadequate engagement of staff across 7 communities
    • Care system designed for crisis intervention
    • Realizing proactive action on trend data is an unmet need

Objective in-home monitoring to identify meaningful behaviours changing during a loneliness intervention

Intervention: "Capturing Time: Journaling Your Journey" -- designed to improve negative emotions such as loneliness, depression, anxiety, and low self-esteem.
Variety of photos and charts.
Austin et al. IEEE Journal of Translational Engineering in Health Medicine 2016

Capturing Time: digital biomarker results

Time waves.
Austin, et al. 2018
  • Loneliness (p<0.05) by an average of 2.2 ± 3 points.
  • Time out-of-home (ß=0.96, p<0.01)
  • Number of computer sessions (IRR=1.196, p<0.01)
  • Walking speed over time (ß = 0.002, p<0.01).
  • Total phone calls, after intervention (IRR=1.003, p<0.01)

Multi-modal Brain Health Program - SHARP: Sharing History through Active Reminiscence and Photo-imagery

Various screenshots.
PI: Raina Croff; NIA: P30AG008017, P30AG024978, and Alzheimer's Association
Croff R, et al. The Gerontologist, 2018.

The "Social Engagement Study" (H. Dodge, PI)
Active, Frequent Assessments & Interventions Delivered Everyday - an RCT to Increase Social Interaction in MCI Using Home-based Technologies

  • 6 week RCT of daily 30 min video chats using Internet connected personal computers with a webcam vs. weekly brief phone interview
  • N = 86; 80.5 ± 6.8 years; MCI & Normal Cognition
  • 89% of all possible sessions completed; Exceptional adherence -- no drop-out
Video Chat screenshots.
Dodge et al. Alzheimer's & Dementia: Translational Res. & Clinical Interventions, 2015
Dodge et al., Current Alzheimer's Disease, 2015

Computer Use: Social Markers of Cognitive Function

Table 4. Average number of words grouped into LIWC categories
LIWC cat. Communication Swear Anger Fillers Family
Avg. num. in MCI 46.4 7.14 37 101.5 31.14
Avg. num. in intact 38.7 4.8 49.8 141.6 41.8
p-value 0.002 0.005 0.054 0.067 0.08
  • MCI participants generate a greater proportion of words (2985 vs. 2423 words on average) out of the total number of words during the conversation sessions (p=0.03).
  • Logistic regression models showed the ROC AUC of identifying MCI (vs. normals) was 0.71 (95% Confidence Interval: 0.54 - 0.89) when average proportion of word counts spoken by subjects was included in the model.
Scatter chart.
Dodge et al. Current Alzheimer Res. 2015 Asgari et al. Alzheimer's & Dementia: Translational Research & Clinical Interventions, 2017

I-CONECT: Internet-based Conversational Engagement Clinical Trials
(PI: Dodge NIA R01AG051628; NIA R01AG056102)

Variety of screenshots.

Teledementia Care: Direct to Home Assessment & Care

  • Alzheimer's Care via Telemedicine -- Establishing the Reliability of Telemedicine-based Measures
  • STAR-C Adapted Telemedicine Intervention
Scatter charts.
Lindauer et al. Dementia Care Comes Home: Patient and Caregiver Assessment via Telemedicine. Gerontologist, 2017.

Ecologically Valid, Ambient, Longitudinal and Unbiased Assessment of Treatment Efficacy in Alzheimer's Disease

  • Longitudinal naturalistic observational cohort study spanning up to 18 months
  • Goal: New Trial Paradigm - Establish Digital Biomarkers that are sensitive to clinical change associated with conventional AD TXs
  • ORCATECH platform
  • Sixty subjects: 30 patients/30 care partners (30 households)
  • NIA / Merck Funding
Week 0 13 26 39 52 65 78
Visit Type Screening Online Phone Online M12 Online M18
Consent X            
Personal & Family History Questionnaire X       X   X
MMSE X       X   X
ISAAC Technology Use Survey X       X   X
Tech & Computer Experience and Proficiency Questionnaires X       X    
Geriatric Depression Scale Short Form (GDS-SF) X       X   X
Zarit Burden Interview (ZBI-12) X X X X X X X
Functional Assessment Questionnaire (FAQ) X X X X X X X
Neuropsychiatric Inventory Questionnaire (NPI-Q) X X X X X X X
Pittsburgh Sleep Quality Assessment (PSQA) X       X   X
ORCATECH Health & Life Activity Form Weekly for duration of study
Caregiving: Time out of home/Time alone in home/Time in same room with partner/Time together in bathroom Assessed continuously
Physical capacity/Mobility: Total daily activity/Mobility/Step count/Walking speed/Time in locations Assessed continuously
Sleep: Time up/Time in Bed/Times Up at Night/Restlessness/Sleep Duration Assessed daily

Couples & Caregiving Analysis: Time spent together

Scatter chart.

Together: 1285 minutes (21.4 hrs/day)
Apart: 155 minutes (2.6 hrs/day)

Reynolds et al., 2017 unpublished
Thomas et al., AAIC 2017

Digital Biomarkers in Later Stage Dementia Interventions

  • ADCS PEACE-AD RCT: Prazocin for Agitation in AD RCT (Pis: Peskind & Raskin; Lim, Reynolds, Kaye)
    • Digital Agitation Assessment - Activity levels monitored continuously during entire 12-wk titration study using wrist actigraphy. Continuous monitoring critical as study employs a flexible dose titration schedule, and the use of rescue medication.
  • MODERATE - Monitoring Dementia-related Agitation using Technology-assisted Evaluations -
    • Multiple sensors used to examine the effects of environment on dementia-associated behaviors.

Thank you!

Please Collaborate -- Your Research Here!

State map.