Competing against firms like Apple and Fitbit, which have dominated the market, Amazon’s Halo will add to its existing branch of smart-powered devices such as Echo speakers and voice software assistant Alexa.
Why does this matter? Halo’s “tone of voice analysis” functionality listens to users’ speech using always-on microphones. In doing this, it aims to track mood and stress levels, determining emotions and indicating users’ overall mental states. The tone of voice data is presented to the user in daily pattern analyses.
Introducing Amazon Halo, a new wearable band and membership that helps you improve your health and wellness. #AmazonHalo
Request early access now ➡️ https://t.co/smPIrmXkEH pic.twitter.com/OvsFYGanHW
— Amazon (@amazon) August 27, 2020
The product may inspire corporates to adopt smart health technology as more companies utilise virtual mental health care platforms to support staff remotely. In addition to its convenience, the device may have added benefits. Wearables like this allegedly produce readings twice as accurate a GP would determine in a face-to-face clinical setting.
Of course, data privacy relating to smart technology is a growing concern. Privacy laws restricting data collection by smart home devices have been proposed in the US and some firms have had to publicly announce they are not utilising data for ulterior purposes.
Data gathering, however, is crucial for product development, particularly with devices integrated with artificial intelligence. Amazon employees have previously listened to users’ Echo devices to assist the training of voice assistant Alexa, for example.
In the workplace, corporate wellness packages often rely heavily on extensive health information, raising questions over employee health data protection and regulation.
Lateral thought from Curation – Wearables may be a key part of preventative health care if they are able to predict deterioration of physical or mental health before a patient would ordinarily visit a GP.
Fitbit, for example, recently showed initial findings that, using its early-stage algorithm, devices were able to detect nearly 50% of positive COVID-19 cases before users showed symptoms by sensing slight changes in users’ heart rate, breathing and sleep patterns.
Katie Chan is ESG Curator at Curation.
