An N/M-Ratio All-Digital Clock Generator with a Pseudo-NMOS Comparator-Based Programmable Divider

A multiplying delay-locked loop (MDLL)-based all-digital clock generator with a programmable N/M-ratio frequency multiplication capability for digital SoC is presented. The proposed digital MDLL provides programmable N/M-ratio frequency multiplication using a new high-speed Pseudo-NMOS comparator-based programmable divider with small area and low power consumption. The proposed MDLL clock generator can also provide a de-skew function by eliminating the phase offset problem caused by the propagation delay of the front divider in conventional N/M MDLL architectures. Fabricated in a 0.13-µm 1.2-V CMOS process, the proposed digital MDLL clock generates fully de-skewed output clock frequencies from 0.3 to 1.137 GHz with programmable N/M ratios of N = 1~32 and M = 1~16. It achieves a measured effective peak-to-peak jitter of 12 ps at 1.0 GHz when N/M = 8/1. It occupies an active area of only 0.034 mm2 and consumes a power of 10.3 mW at 1.0 GHz.

Extended Application of Digital Clock Drawing Test in the Evaluation of Alzheimer’s Disease Based on Artificial intelligence and the Neural Basis

Introduction: This study aimed to build the supervised learning model to predict the state of cognitive impairment, Alzheimer’s Disease (AD) and cognitive domains including memory, language, action, and visuospatial based on Digital Clock Drawing Test (dCDT) precisely. Methods: 207 normal controls, 242 Mild Cognitive Impairment (MCI) patients, 87 dementia patients, including 53 AD patients, were selected from Shanghai Tongji Hospital. The electromagnetic tablets were used to collect the trajectory points of dCDT. By combining dynamic process and static results, different types of features were extracted, and the prediction models were built based on the feature selection approaches and machine learning methods. Results: The optimal AUC of cognitive impairment’s screening, AD’s screening and differentiation are 0.782, 0.919 and 0.818, respectively. In addition, the cognitive state of the domains with the best prediction result based on the features of dCDT is action with the optimal AUC 0.794, while the other three cognitive domains got the prediction results between 0.744-0.755. Discussion: By extracting dCDT features, cognitive impairment and AD patients can be identified early. Through dCDT feature extraction, a prediction model of single cognitive domain damage can be established.

Are Analogue or Digital Clocks Friendlier for People Living with Dementia?

<b><i>Background:</i></b> In ageing population, it is desirable to reduce the impact of cognitive decline on daily life. While various types of dementia-friendly environments have been proposed, the question still remains regarding whether analogue or digital clocks are friendlier for people with dementia. <b><i>Methods:</i></b> In clinical practice, we normally use our original clock reading test (10 analogue and 10 digital clocks) to assess patients’ ability to read a clock. In the present study, a retrospective medical record survey was conducted. Fifty-five participants who had done the test were identified. The result of the test was compared between analogue and digital clocks. Additionally, to assess specific ability to read analogue clocks, an “analogue-digital gap” was defined as the difference between patients’ performance for analogue and digital clocks. Univariate and multivariate analyses were conducted to detect significant factors associated with reading ability specific to analogue clocks. <b><i>Results:</i></b> The analogue clock proved less readable than the digital clock, even after adjusting for MMSE total score (<i>p</i> = 0.003). Multivariate analysis revealed reading ability of the analogue clock was significantly associated with MMSE calculation and clock drawing test (<i>p</i> = 0.009 and 0.040, respectively). <b><i>Conclusions:</i></b> In the present study, the digital clock was friendlier than the analogue clock for patients with dementia. Compared to the digital clock, reading analogue clocks might require more widespread cognition, such as working memory and visuospatial processing. While our finding was a general tendency, and individual assessment is necessary, it might help the development of personalized environmental adjustments.

Arduino Digital Clock without RTC Module

This paper analyzes a clock using Arduino without Real time clock (RTC). The development of the digital clock in Arduino is to provide its own time without RTC. Generally, electronic circuit designers use RTC to construct a clock. Such a circuit requires an extra circuit and power. The CMOS battery supplies power to the RTC, once the CMOS battery power is discharged. It automatically erases the date and time and requires an update from an external device. Considering these facts, RTC is avoided and code with nested looping is used to maintain timing in Arduino. It enables us to modify the time using a keypad and LCD without an external device. Continuous power is supplied to the Arduino using a battery backup. Such a circuit is simple with reduced code. All features available in RTC are available in this circuit. Keywords: Arduino Atmega 328P, RTC, LCD16 x 2, Keypad 4x3.

Classifying Non-Dementia and Alzheimer’s Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test

Background: Advantages of digital clock drawing metrics for dementia subtype classification needs examination. Objective: To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer’s disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer’s disease (AD) versus vascular dementia (VaD). Methods: Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer’s disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models. Results: When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features. Conclusion: The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

Normative References for Graphomotor and Latency Digital Clock Drawing Metrics for Adults Age 55 and Older: Operationalizing the Production of a Normal Appearing Clock

Background: Relative to the abundance of publications on dementia and clock drawing, there is limited literature operationalizing ‘normal’ clock production. Objective: To operationalize subtle behavioral patterns seen in normal digital clock drawing to command and copy conditions. Methods: From two research cohorts of cognitively-well participants age 55 plus who completed digital clock drawing to command and copy conditions (n = 430), we examined variables operationalizing clock face construction, digit placement, clock hand construction, and a variety of time-based, latency measures. Data are stratified by age, education, handedness, and number anchoring. Results: Normative data are provided in supplementary tables. Typical errors reported in clock research with dementia were largely absent. Adults age 55 plus produce symmetric clock faces with one stroke, with minimal overshoot and digit misplacement, and hands with expected hour hand to minute hand ratio. Data suggest digitally acquired graphomotor and latency differences based on handedness, age, education, and anchoring. Conclusion: Data provide useful benchmarks from which to assess digital clock drawing performance in Alzheimer’s disease and related dementias.