Diagnosis and monitoring of Alzheimer's patients using classical and deep learning techniques

Machine based analysis and prediction systems are widely used for diagnosis of Alzheimer's Disease (AD). However, lower accuracy of existing techniques and lack of post diagnosis monitoring systems limit the scope of such studies. In this paper, a novel machine learning based diagnosis and monitoring of AD-like diseases is proposed. The AD-like diseases diagnosis process is accomplished by analysing the magnetic resonance imaging (MRI) scans using deep learning and is followed by an activity monitoring framework to monitor the subjects’ activities of daily living using body worn inertial sensors. The activity monitoring provides an assistive framework in daily life activities and evaluates vulnerability of the patients based on the activity level. The AD diagnosis results show up to 82% improvement in comparison to well-known existing techniques. Moreover, above 95% accuracy is achieved to classify the activities of daily living which is quite encouraging in terms of monitoring the activity profile of the subject

The use of wearable/portable digital sensors in Huntington’s disease: a systematic review

In chronic neurological conditions, wearable/portable devices have potential as innovative tools to detect subtle early disease manifestations and disease fluctuations for the purpose of clinical diagnosis, care and therapeutic development. Huntington’s disease (HD) has a unique combination of motor and non-motor features which, combined with recent and anticipated therapeutic progress, gives great potential for such devices to prove useful. The present work aims to provide a comprehensive account of the use of wearable/portable devices in HD and of what they have contributed so far. We conducted a systematic review searching MEDLINE, Embase, and IEEE Xplore. Thirty references were identified. Our results revealed large variability in the types of sensors used, study design, and the measured outcomes. Digital technologies show considerable promise for therapeutic research and clinical management of HD. However, more studies with standardized devices and harmonized protocols are needed to optimize the potential applicability of wearable/portable devices in HD

the wearable devices opportunity

학위논문(박사) -- 서울대학교대학원 : 의과대학 의학과, 2022. 8. 김기웅.배경 및 목적: 치매로 인한 공공보건 부담이 가중됨에도 만족스러운 치료법은 부재한 현 상황은 치매 발병을 예방하거나 진행을 지연시키기 위해 인지저하 또는 치매 위험이 있는 사람들을 조기에 식별해야 할 필요를 더욱 부각시킨다. 최근 연구들은 보행 시 한발-한발 사이 보행인자들의 변동성을 의미하는 보행변이성이 인지 저하, 경도인지장애 및 치매의 위험과 밀접하게 관련되어 있다는 것을 보였다. 특히 웨어러블 센서를 통해 얻은 보행변이성은 감독이 없는 자연스러운 환경에서 더 오랜 기간 동안 측정값을 낮은 비용으로 얻을 수 있다는 실용적인 이점으로 인해 인지저하의 위험을 예측하는 유망한 디지털 바이오마커로 활용될 수 있다. 본 논문에서는, 신체에 부착한 단일 삼축가속계로 측정된 보행 변이성이 미래의 인지저하 위험을 예측하는 디지털 바이오마커로 사용될 수 있을지에 대해 연구하였다. 첫 번째 연구에서는 신체 부착 삼축가속계로 얻은 보행변이성이 정상인지를 가진 노인에서 미래 인지저하의 위험을 예측할 수 있는지를 조사했다. 두 번째 연구에서는 더 큰 표본 크기와 더 넓은 범위의 인지 기능을 가진 비치매 노인을 대상으로, 디지털 바이오마커로서 보행 변이성의 가능성을 이론적으로 뒷받침할 수 있는 신경기질에 대해 조사하였다. 또한, 높은 보행 변이성이 인지 기능 및 기억 기능에 관련된 것으로 밝혀진 뇌 영역에서의 얇아진 대뇌 피질 두께와 관련되어 있을 것이며, 그 영역이 보행-인지 사이의 연관성을 설명하는 공유 신경 기질에 해당할 것이라는 가설을 검증하였다. 방법: 연구 I에서 우리는 뇌허혈이나 파킨슨병이 없으면서, 지역사회에 거주하는, 인지적으로 정상인 노인 91명을 대상으로 4년 전향적 코호트 연구를 수행하였다. 체중심에 부착한 삼축가속계를 이용하여 보행변이성을 측정하였고, 경도인지장애에 관한 국제 워킹 그룹의 진단기준에 따라 경도인지 장애를 진단했다. 우리는 보행 변이성의 크기에 따라 연구대상자를 삼분위수로 분류하여, 보행변이성이 가장 큰 일분위 그룹과 나머지 그룹을 관찰하며 4년 동안의 경도인지장애의 발병을 추적하였다. 그룹간 경도인지장애 발병 위험 비교는 Log-rank test와 Kaplan-Meier 분석을 통해 수행했다. 경도인지장애 발병 위험비(Hazard Ratio, HR)는 연령, 성별, 교육수준, 누적질병평가척도 점수, GDS 점수, 아포지단백 E ε4 대립유전자 유무를 보정한 콕스 비례위험 회귀 분석을 사용하여 추정하였다. 연구 II에서 우리는 207명의 치매가 없는 노인을 대상으로, 보행변이성과 연관된 뇌 피질 및 피질 하 신경 구조, 보행변이성-인지기능의 공유신경기질을 횡단적으로 연구하였다. 자기공명영상에서 뇌 피질의 두께와 피질 하 구조물 부피를 구하여 보행변이성, 인지기능, 피질 두께와 피질 하 구조물 부피와의 연관성을 각각 조사했다. 또한 보행변이성과 인지기능 양쪽에 모두 유의한 연관성을 보이는 뇌영역의 피질 두께 또는 피질 하 구조물 부피가 실제로 보행변이성과 인지기능 관계에 미치는 매개효과를 분석하였다. 결과: 연구 I에서 보행변이성이 일분위에 속하는 노인들은 나머지 노인들에 비해서 4년 간 경도인지장애 발병 위험이 약 12배 더 높았다. (HR = 11.97, 95% CI = 1.29–111.37). 그러나 느린 보행 속도를 가진 노인들은 나머지 노인들과 비슷한 경도인지장애 발병위험을 보였다. (HR = 5.04, 95% CI = 0.53–48.18). 우리는 또한 보행변이성이 미래 인지저하를 예측하는 것에는 성별에 따른 차이가 유의하지 않다는 것을 밝혔다. 연구 대상자들을 보행변이성의 크기로 삼분위화 하는 과정에서의 역치효과 (threshold effect) 유무를 알아보기 위해, 보행변이성과 보행속도를 연속변수로 두고 분석하였을 때에도 보행변이성이 10% 증가할 때마다 인지저하의 위험이 1.5배 증가하는 반면 보행속도의 변화에 따라 인지감퇴 위험의 유의한 변화는 없었다. 연구 II에서 높은 보행변이성은 낮은 인지기능과 관련이 있었다. 우리는 높은 보행변이성이 광범위한 영역에서 대뇌피질 두께 감소와 연관이 있다는 것을 확인했다. 반면, 보행변이성은 피질 하 구조물의 부피와는 유의한 연관성을 보이지 않았다. 보행변이성과 유의한 상관관계를 보인 피질 클러스터 중 좌반구의 inferior temporal, entorhinal, parahippocampal, fusiform, and lingual을 포함하는 클러스터의 피질 두께는 전반적 인지기능 및 언어기억기능과 연관이 있었다. 결론 및 해석: 결론적으로 본 연구는, 신체부착 단일 삼축가속계로 측정한 보행변이성의 인지저하 위험 예측 디지털 바이오마커로서의 가능성에 근거를 제시하고 있다.Background and Objectives: Large public health burden of dementia and the absence of a cure highlight the need for early identification of those at risk for cognitive decline or dementia to prevent and/or delay the onset of dementia. Emerging evidence indicates gait variability, the fluctuation of a gait measure from one step to the next, strongly relate to the risk of cognitive decline, MCI and dementia. Gait variability obtain via wearable sensor is a promising digital biomarker for predicting risk of cognitive impairment due to its favorable practical advantages of being able to obtain measurements over a longer period of time under unsupervised real-world conditions at lower cost. In my thesis, I examine the possibility that gait variability measured by a single body-worn tri-axial accelerometer (TAA) can be used as a digital biomarker to predict future risk of cognitive decline. In the first study, I examined whether gait variability obtained by the body-worn TAA could predict future risk of cognitive decline in older people with normal cognition (NC). In the second study, I then identify neural substrates that theoretically support the potential of gait variability as a digital biomarker in older adults with larger sample size and broader range of cognitive function. Additionally, I hypothesized higher gait variability would be related to lower cortical thickness, especially in regions important for cognitive function and memory, and that these regions would represent a shared neural substrate for gait control and cognitive impairment. Methods: In the study I, we conducted 4-year prospective cohort study on 91 community-dwelling cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism. We evaluated gait speed and step time variability using a TAA placed on the center of body mass, and diagnosed mild cognitive impairment (MCI) according to the International Working Group on MCI. We performed Kaplan-Meier analysis with consecutive log-rank testing for MCI-free survival by cohort-specific tertiles of gait variability; hazard ratios (HR) of incident MCI were estimated using Cox proportional hazards regression analysis adjusted for age, sex, education level, Cumulative Illness Rating Scale score, GDS score, and presence of the apolipoprotein E ε4 allele. In the study II, we cross-sectionally investigated the cortical and subcortical neural structures associated with gait variability, and the shared neural substrates of gait variability and cognitive function in 207 non-demented older adults. We obtained the cortical thickness and subcortical volumes from the magnetic resonance images, and examined associations between gait variability, cognitive function, and cortical thickness and subcortical volumes. Finally, we analyzed the mediation effect of the cluster cortical thickness and subcortical volume which had a significant association with both gait variability and cognitive function on the association between gait variability and cognition. Results: In the study I, subjects with high gait variability showed about 12-fold higher risk of MCI (HR = 11.97, 95% CI = 1.29–111.37) than those with mid-to-low variability. However, those with slow gait speed showed comparable MCI risk to those with mid-to-high speed (HR = 5.04, 95% CI = 0.53– 48.18). We additionally found that no sex differences were found when assessing the ability of high gait variability to predict future cognitive decline. When we computed gait variability and gait speed as continuous variables to explore whether there are any threshold effects, the risk of incident cognitive decline increased 1.5 times per 10% increment of gait variability, whereas it did not change significantly with changes of gait speed. In the study II, higher gait variability was associated with lower cognitive functions. We found the widespread decrease in cortical thickness with increasing gait variability while there was no significant association with the volume of subcortical structures. Among the clusters that showed significant correlation with the gait variability, a cluster that included the inferior temporal, entorhinal, parahippocampal, fusiform, and lingual in left hemisphere was also associated with global cognitive function, and verbal memory function. Cortical thickness of the cluster explained 17% of the total effect of gait variability on global cognitive function measured by CERAD-TS. Interpretation: Gait variability measured by a single body-worn TAA could be a novel digital biomarker of risk of cognitive decline that could be used repeatedly and frequently and at low cost to test risk of individuals without clinical evidence of cognitive impairments.I Introduction 10 1. Study background 11 2. Purpose of research 16 II Methods 18 1. Study 1: Can gait variability predict the risk of cognitive decline in cognitively normal elderly? 19 1.1. Study population 19 1.2. Clinical assessments 20 1.3. Gait Assessments 22 1.4. Statistical analysis 23 2. Study 2: Shared Neural Substrates between Gait Variability-Cognitive Function 24 2.1. Study population 24 2.2. Assessments of cognition and medical conditions 25 2.3. Gait assessments 26 2.4. Magnetic resonance imaging (MRI) acquisition and preprocessing 27 2.5. Statistical analyses 28 III Results 32 1. Study 1: Can gait variability predict the risk of cognitive decline in cognitively normal elderly? 33 1.1. Association of gait variability and gait speed status with the risk of MCI 34 2. Study 2: Shared Neural Substrates between Gait Variability-Cognitive Function 35 IV Discussion 38 [Figure 1] Risk of incident mild cognitive impairment over 4 years stratified by gait speed (a) and variability (b) by log-rank test 49 [Figure 2] Cortical thickness and gait variability in non-demented older adults 50 [Figure 3] Cortical thickness of LH1 cluster mediates effect of gait variability on CERAD-TS (a) and VMS (b) 51 [Table 1] Demographic, clinical, cognitive function, and gait characteristics of the subjects 52 [Table 2] Prediction of mild cognitive impairment in cognitively normal elderly individuals 54 [Table 3] Characteristics of participants 55 [Table 4] Vertex-Wise Analyses of Gait Variability and Cortical Thickness 56 [Table 5] Regression Analyses of Gait Variability and Cortical Thickness 57 [Table 6] Associations between Cortical Regions related with Gait Variability and Cognitive Function 58 Bibliography 59 감사의 글 66 초 록 67박

Evaluation of home-based rehabilitation sensing systems with respect to standardised clinical tests

With increased demand for tele-rehabilitation, many autonomous home-based rehabilitation systems have appeared recently. Many of these systems, however, suffer from lack of patient acceptance and engagement or fail to provide satisfactory accuracy; both are needed for appropriate diagnostics. This paper first provides a detailed discussion of current sensor-based home-based rehabilitation systems with respect to four recently established criteria for wide acceptance and long engagement. A methodological procedure is then proposed for the evaluation of accuracy of portable sensing home-based rehabilitation systems, in line with medically-approved tests and recommendations. For experiments, we deploy an in-house low-cost sensing system meeting the four criteria of acceptance to demonstrate the effectiveness of the proposed evaluation methodology. We observe that the deployed sensor system has limitations in sensing fast movement. Indicators of enhanced motivation and engagement are recorded through the questionnaire responses with more than 83% of the respondents supporting the system’s motivation and engagement enhancement. The evaluation results demonstrate that the deployed system is fit for purpose with statistically significant ( ϱc>0.99 , R2>0.94 , ICC>0.96 ) and unbiased correlation to the golden standard

Protocol for PD SENSORS:Parkinson’s Disease Symptom Evaluation in a Naturalistic Setting producing Outcomes measuRes using SPHERE technology. An observational feasibility study of multi-modal multi-sensor technology to measure symptoms and activities of daily living in Parkinson’s disease

Introduction The impact of disease-modifying agents on disease progression in Parkinson’s disease is largely assessed in clinical trials using clinical rating scales. These scales have drawbacks in terms of their ability to capture the fluctuating nature of symptoms while living in a naturalistic environment. The SPHERE (Sensor Platform for HEalthcare in a Residential Environment) project has designed a multi-sensor platform with multimodal devices designed to allow continuous, relatively inexpensive, unobtrusive sensing of motor, non-motor and activities of daily living metrics in a home or a home-like environment. The aim of this study is to evaluate how the SPHERE technology can measure aspects of Parkinson’s disease.Methods and analysis This is a small-scale feasibility and acceptability study during which 12 pairs of participants (comprising a person with Parkinson’s and a healthy control participant) will stay and live freely for 5 days in a home-like environment embedded with SPHERE technology including environmental, appliance monitoring, wrist-worn accelerometry and camera sensors. These data will be collected alongside clinical rating scales, participant diary entries and expert clinician annotations of colour video images. Machine learning will be used to look for a signal to discriminate between Parkinson’s disease and control, and between Parkinson’s disease symptoms ‘on’ and ‘off’ medications. Additional outcome measures including bradykinesia, activity level, sleep parameters and some activities of daily living will be explored. Acceptability of the technology will be evaluated qualitatively using semi-structured interviews.Ethics and dissemination Ethical approval has been given to commence this study; the results will be disseminated as widely as appropriate