Harnessing Speech-Derived Digital Biomarkers to Detect and Quantify Cognitive Decline Severity in Older Adults.

INTRODUCTION: Current cognitive assessments suffer from floor/ceiling and practice effects, poor psychometric performance in mild cases, and repeated assessment effects. This study explores the use of digital speech analysis as an alternative tool for determining cognitive impairment. The study specifically focuses on identifying the digital speech biomarkers associated with cognitive impairment and its severity. METHODS: We recruited older adults with varying cognitive health. Their speech data, recorded via a wearable microphone during the reading aloud of a standard passage, were processed to derive digital biomarkers such as timing, pitch, and loudness. Cohen's d effect size highlighted group differences, and correlations were drawn to the Montreal Cognitive Assessment (MoCA). A stepwise approach using a Random Forest model was implemented to distinguish cognitive states using speech data and predict MoCA scores based on highly correlated features. RESULTS: The study comprised 59 participants, with 36 demonstrating cognitive impairment and 23 serving as cognitively intact controls. Among all assessed parameters, similarity, as determined by Dynamic Time Warping (DTW), exhibited the most substantial positive correlation (rho = 0.529, p < 0.001), while timing parameters, specifically the ratio of extra words, revealed the strongest negative correlation (rho = -0.441, p < 0.001) with MoCA scores. Optimal discriminative performance was achieved with a combination of four speech parameters: total pause time, speech-to-pause ratio, similarity via DTW, and intelligibility via DTW. Precision and balanced accuracy scores were found to be 88.1 ± 1.2% and 76.3 ± 1.3%, respectively. DISCUSSION: Our research proposes that reading-derived speech data facilitates the differentiation between cognitively impaired individuals and cognitively intact, age-matched older adults. Specifically, parameters based on timing and similarity within speech data provide an effective gauge of cognitive impairment severity. These results suggest speech analysis as a viable digital biomarker for early detection and monitoring of cognitive impairment, offering novel approaches in dementia care.

Care4AD: A Technology-Driven Platform for Care Coordination and Management: Acceptability Study in Dementia.

INTRODUCTION: The technology-driven solution can reduce the caregiving burden; however, the needs of dementia caregiving are unique, and attitudes towards adopting technology from the perspectives of all the stakeholders involved in dementia caregiving are unclear. This study aims to assess the acceptability and feasibility of a technology-driven platform to facilitate care coordination platform, Care4AD, from the end-user perspective. METHODS: Care4AD includes three components: (1) Care4AD app: the app is used by caregivers to coordinate care, monitor physical activity, and schedule reminders; (2) Care4AD tablet: a smart tablet is used by the care recipient to display scheduled reminders; and (3) Care4AD tags: a series of wireless sensor tags attached to various objects of daily care to facilitate monitoring instrumental activities of daily living (IADL) and adherence to scheduled tasks. Stakeholders in caregiving, including 11 experts in dementia care (age: 53.3 ± 8, 73% female), 10 individuals with dementia (IWD) (age: 76.1 ± 7.3, 50% female), and 14 caregivers (age: 66.9 ± 10.6, 75% female) were interviewed to determine perceived ease of use, attitude towards use, and perceived usefulness, based on the technology acceptance model (TAM) questionnaire. Additionally, we assessed technology anxiety and concerns with data sharing by caregivers and IWD. The interviews were conducted through videoconferencing or in-person meetings. The interview was composed of open-ended questions, a demonstration of the proposed Care4AD platform, and a survey based on TAM. RESULTS: Compared to the neutral response, stakeholders showed significantly higher acceptance (70-100% satisfied to highly satisfied, p < 0.05) for all components of the TAM. Among IWD, age (r = -0.68, p = 0.03) and for caregivers the perceived ease of use (r = 0.73, p < 0.01) were significant predictors of attitude towards using the technology. Interestingly, neither concerns about data sharing nor educational level were limiting factors in the acceptability of the system in our sample. CONCLUSION: Overall, the results support a high perception of usefulness, ease of use, and attitude towards using Care4AD. The key barriers to adopting such technology are the age of IWD and the caregiver's perception of ease of use. Future studies are warranted to explore the effectiveness of such a platform to reduce caregiver stress and improve the quality of life and independence of IWD.

Smart-Home Concept for Remote Monitoring of Instrumental Activities of Daily Living (IADL) in Older Adults with Cognitive Impairment: A Proof of Concept and Feasibility Study.

Assessment of instrumental activities of daily living (IADL) is essential for the diagnosis and staging of dementia. However, current IADL assessments are subjective and cannot be administered remotely. We proposed a smart-home design, called IADLSys, for remote monitoring of IADL. IADLSys consists of three major components: (1) wireless physical tags (pTAG) attached to objects of interest, (2) a pendant-sensor to monitor physical activities and detect interaction with pTAGs, and (3) an interactive tablet as a gateway to transfer data to a secured cloud. Four studies, including an exploratory clinical study with five older adults with clinically confirmed cognitive impairment, who used IADLSys for 24 h/7 days, were performed to confirm IADLSys feasibility, acceptability, adherence, and validity of detecting IADLs of interest and physical activity. Exploratory tests in two cases with severe and mild cognitive impairment, respectively, revealed that a case with severe cognitive impairment either overestimated or underestimated the frequency of performed IADLs, whereas self-reporting and objective IADL were comparable for the case with mild cognitive impairment. This feasibility and acceptability study may pave the way to implement the smart-home concept to remotely monitor IADL, which in turn may assist in providing personalized support to people with cognitive impairment, while tracking the decline in both physical and cognitive function.

Digital Biomarkers for the Objective Assessment of Disability in Neurogenic Thoracic Outlet Syndrome.

Neurogenic thoracic outlet syndrome (nTOS) is a musculoskeletal disorder in which compression of the brachial plexus between the scalene muscles of the neck and the first rib results in disabling upper extremity pain and paresthesia. Currently there are no objective metrics for assessing the disability of nTOS or for monitoring response to its therapy. We aimed to develop digital biomarkers of upper extremity motor capacity that could objectively measure the disability of nTOS using an upper arm inertial sensor and a 20-s upper extremity task that provokes nTOS symptoms. We found that digital biomarkers of slowness, power, and rigidity statistically differentiated the affected extremities of patients with nTOS from their contralateral extremities (n = 16) and from the extremities of healthy controls (n = 13); speed and power had the highest effect sizes. Digital biomarkers representing slowness, power, and rigidity correlated with patient-reported outcomes collected with the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire and the visual analog scale of pain (VAS); speed had the highest correlation. Digital biomarkers of exhaustion correlated with failure of physical therapy in treating nTOS; and digital biomarkers of slowness, power, and exhaustion correlated with favorable response to nTOS surgery. In conclusion, sensor-derived digital biomarkers can objectively assess the impairment of motor capacity resultant from nTOS, and correlate with patient-reported symptoms and response to therapy.