A tutorial on human activity recognition using body-worn inertial sensors
The last 20 years have seen ever-increasing research activity in the field of human activity
recognition. With activity recognition having considerably matured, so has the number of …
recognition. With activity recognition having considerably matured, so has the number of …
Designing wearable systems for sports: a review of trends and opportunities in human–computer interaction
This paper presents a literature review of human-computer interaction works on wearable
systems for sports. We selected a corpus of 57 papers and analyzed them through the …
systems for sports. We selected a corpus of 57 papers and analyzed them through the …
Ensembles of deep lstm learners for activity recognition using wearables
Recently, deep learning (DL) methods have been introduced very successfully into human
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …
activity recognition (HAR) scenarios in ubiquitous and wearable computing. Especially the …
Deep recurrent neural network for mobile human activity recognition with high throughput
In this paper, we propose a method of human activity recognition with high throughput from
raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate …
raw accelerometer data applying a deep recurrent neural network (DRNN), and investigate …
PD disease state assessment in naturalistic environments using deep learning
Abstract Management of Parkinson's Disease (PD) could be improved significantly if
reliable, objective information about fluctuations in disease severity can be obtained in …
reliable, objective information about fluctuations in disease severity can be obtained in …
Personalized human activity recognition based on integrated wearable sensor and transfer learning
Human activity recognition (HAR) based on the wearable device has attracted more
attention from researchers with sensor technology development in recent years. However …
attention from researchers with sensor technology development in recent years. However …
Optimising sampling rates for accelerometer-based human activity recognition
Real-world deployments of accelerometer-based human activity recognition systems need
to be carefully configured regarding the sampling rate used for measuring acceleration …
to be carefully configured regarding the sampling rate used for measuring acceleration …
Bootstrapping human activity recognition systems for smart homes from scratch
SK Hiremath, Y Nishimura, S Chernova… - Proceedings of the ACM …, 2022 - dl.acm.org
Smart Homes have come a long way: From research laboratories in the early days, through
(almost) neglect, to their recent revival in real-world environments enabled through the …
(almost) neglect, to their recent revival in real-world environments enabled through the …
Movement recognition technology as a method of assessing spontaneous general movements in high risk infants
Preterm birth is associated with increased risks of neurological and motor impairments such
as cerebral palsy. The risks are highest in those born at the lowest gestations. Early …
as cerebral palsy. The risks are highest in those born at the lowest gestations. Early …
HMGAN: A hierarchical multi-modal generative adversarial network model for wearable human activity recognition
Wearable Human Activity Recognition (WHAR) is an important research field of ubiquitous
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …
and mobile computing. Deep WHAR models suffer from the overfitting problem caused by …