Multi-Modal Wireless Flexible Gel-Free Sensors with Edge Deep Learning for Detecting and Alerting Freezing of Gait in Parkinson's Patients

Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease (PD). This work develops flexible wearable sensors that can detect FoG and alert patients and companions to help prevent falls. FoG is detected on the sensors using a deep learning (DL) model with multi-modal sensory inputs collected from distributed wireless sensors. Two types of wireless sensors are developed, including: (1) a C-shape central node placed around the patient's ears, which collects electroencephalogram (EEG), detects FoG using an on-device DL model, and generates auditory alerts when FoG is detected; (2) a stretchable patch-type sensor attached to the patient's legs, which collects electromyography (EMG) and movement information from accelerometers. The patch-type sensors wirelessly send collected data to the central node through low-power ultra-wideband (UWB) transceivers. All sensors are fabricated on flexible printed circuit boards. Adhesive gel-free acetylene carbon black and polydimethylsiloxane electrodes are fabricated on the flexible substrate to allow conformal wear over the long term. Custom integrated circuits (IC) are developed in 180 nm CMOS technology and used in both types of sensors for signal acquisition, digitization, and wireless communication. A novel lightweight DL model is trained using multi-modal sensory data. The inference of the DL model is performed on a low-power microcontroller in the central node. The DL model achieves a high detection sensitivity of 0.81 and a specificity of 0.88. The developed wearable sensors are ready for clinical experiments and hold great promise in improving the quality of life of patients with PD. The proposed design methodologies can be used in wearable medical devices for the monitoring and treatment of a wide range of neurodegenerative diseases

The Evolution of Top Incomes: A Historical and International Perspective

This paper summarizes the main findings of the recent studies that have constructed top income and wealth shares series over the century for a number of countries using tax statistics. Most countries experience a dramatic drop in top income shares in the first part of the century due to a precipitous drop in large wealth holdings during the wars and depression shocks. Top income shares do not recover in the immediate post war decades. However, over the last 30 years, top income shares have increased substantially in English speaking countries but not at all in continental Europe countries or Japan. This increase is due to an unprecedented surge in top wage incomes starting in the 1970s and accelerating in the 1990s. As a result, top wage earners have replaced capital income earners at the top of the income distribution in English speaking countries. We discuss the proposed explanations and the main questions that remain open.

The effect of entrepreneurial activity on national economic growth

Entrepreneurial activity is generally assumed to be an important aspect of the organization of industries most conducive to innovative activity and unrestrained competition. This paper investigates whether total entrepreneurial activity influences GDP growth for a sample of 36 countries. We test whether this influence depends on the level of economic development measured as GDP per capita. Adjustment is made for a range of alternative explanations for achieving economic growth by incorporating the Growth Competitiveness Index. We find that entrepreneurial activity by nascent entrepreneurs and owner/managers of young businesses affects economic growth, but that this effect depends upon the level of per capita income. This suggests that entrepreneurship plays a different role in countries in different stages of economic development.

Guide to the Alton Augustus Adams, Sr. Collection

The Alton Augustus Adams, Sr. Collection reflects his activities as a bandmaster, a press correspondent, activities in the Hotel Association of the Virgin Islands, and as educator, civic leader, composer, author, and local historian in St. Thomas, Virgin Islands.https://digitalcommons.colum.edu/cmbr_guides/1000/thumbnail.jp

20th Annual Academic Honors Program

May 4, 1984https://digitalcommons.cedarville.edu/honors_day_programs/1042/thumbnail.jp

Ego-Body Pose Estimation via Ego-Head Pose Estimation

Estimating 3D human motion from an egocentric video sequence is critical to human behavior understanding and applications in VR/AR. However, naively learning a mapping between egocentric videos and human motions is challenging, because the user's body is often unobserved by the front-facing camera placed on the head of the user. In addition, collecting large-scale, high-quality datasets with paired egocentric videos and 3D human motions requires accurate motion capture devices, which often limit the variety of scenes in the videos to lab-like environments. To eliminate the need for paired egocentric video and human motions, we propose a new method, Ego-Body Pose Estimation via Ego-Head Pose Estimation (EgoEgo), that decomposes the problem into two stages, connected by the head motion as an intermediate representation. EgoEgo first integrates SLAM and a learning approach to estimate accurate head motion. Then, taking the estimated head pose as input, it leverages conditional diffusion to generate multiple plausible full-body motions. This disentanglement of head and body pose eliminates the need for training datasets with paired egocentric videos and 3D human motion, enabling us to leverage large-scale egocentric video datasets and motion capture datasets separately. Moreover, for systematic benchmarking, we develop a synthetic dataset, AMASS-Replica-Ego-Syn (ARES), with paired egocentric videos and human motion. On both ARES and real data, our EgoEgo model performs significantly better than the state-of-the-art.Comment: project website: https://lijiaman.github.io/projects/egoego

The effect of entrepreneurial activity on national economic growth

Entrepreneurial activity is generally assumed to be an important aspect of the organization of industries most conducive to innovative activity and unrestrained competition. This paper investigates whether total entrepreneurial activity influences GDP growth for a sample of 36 countries. We test whether this influence depends on the level of economic development measured as GDP per capita. Adjustment is made for a range of alternative explanations for achieving economic growth by incorporating the Growth Competitiveness Index. We find that entrepreneurial activity by nascent entrepreneurs and owner/managers of young businesses affects economic growth, but that this effect depends upon the level of per capita income. This suggests that entrepreneurship plays a different role in countries in different stages of economic development