Abstract-Handgrip contractions are a standard exercise modality to evaluate cardiovascular system performance. Most conventional ergometer systems of this nature are manually controlled, placing a burden on the researcher to guide subject activity while recording the resultant data. This paper presents updates to a hand-forearm ergometer system that automate the control and data-acquisition processes. A LabVIEW virtual instrument serves as the centerpiece for the system, providing the subject/researcher interfaces as well as coordinating data acquisition from both traditional and new sensors. Initial data indicate the viability of the system with regard to its ability to obtain consistent and physiologically meaningful data.
The results of the present investigation highlight the potential utility of V̇O2max, particularly as it relates to the metabolic demands of a surface ambulation, in defining successful completion of planetary-based exploration field tests.
Behavior tracking with severely disabled children can be a challenge, since dealing directly with a child's behavior is more immediately pressing than the need to record an event for tracking purposes. By the time a paraeducator (`para') is able to break away and record events, behavior counts can be forgotten. This paper presents a paraeducator glove design that can help to track behaviors with minimal distraction by allowing a paraeducator to touch their thumb to one of their other four fingers, where each finger represents a different behavior. Count data are packaged by a microcontroller board on the glove and then sent wirelessly to a smart phone via a Bluetooth Low Energy (BLE) link. A customized BLE profile was designed for this application to promote real-time recording. These data can be forwarded to a database for further analysis. This para glove design addresses basic needs of a wearable device that employs BLE, including local data collection, BLE data transmission, and remote data recording. More functional sensors can be added to this platform to support other wearable scenarios.
An automated hand-forearm ergometer with realtime data analysis would be a helpful tool to evaluate muscle fatigue mid-experiment, offering insights into changes in electromyogram parameters that can be used to track fatigue in the hand and forearm musculature. This work presents real-time additions to a custom, automated hand-forearm ergometer that will perform mid-experiment signal processing and help to identify fatigue onset and predict task failure.
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