Evidence map›Paper›PMID 39774277›Full record

ArticleScientific reports2025

Tuning into urban birdsong: enhancing nature connectedness with an AI-powered wearable.

Zhuying Li, Si Cheng, Xiaoqing Sun, Xipei Ren, Yan Wang, Min-Ling Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhuying LiSchool of Computer Science and Engineering, Southeast University, Nanjing, China. zhuyingli@seu.edu.cn.ORCID 0000-0001-5474-6949
Si ChengSchool of Computer Science and Engineering, Southeast University, Nanjing, China.
Xiaoqing SunSchool of Design and Arts, Beijing Institute of Technology, Beijing, China.
Xipei RenSchool of Design and Arts, Beijing Institute of Technology, Beijing, China.
Yan WangNan Tien Institute, Berkeley, Australia.
Min-Ling ZhangSchool of Computer Science and Engineering, Southeast University, Nanjing, China.

Funding

National Natural Science Foundation of China (National Science Foundation of China) No.62302094
6 · The paper itself

Abstract

The rapid urbanization has led to the loss of natural spaces and a subsequent disconnection between humans and nature, negatively affecting residents' well-being and environmental awareness. There is a a growing interest in leveraging technology to address this gap in Human-Computer Interaction. This article introduces GoChirp, an AI-powered wearable device for enhancing nature relatedness within urban landscapes. By utilizing machine learning algorithms, GoChirp recognizes bird sounds in the environment and provides haptic feedback that mimics the bird flapping, directing users' attention to avian life and fostering a heightened awareness and connection to nature. To evaluate GoChirp, we conducted a week-long field study with 36 urban participants divided into two groups: an experimental group using GoChirp and a control group using a dummy device. We used pre- and post-study questionnaires to assess changes in participants' nature relatedness. Additional questionnaires and semi-structured interviews were employed to evaluate the device's usability and user experience. The results suggest that AI-powered wearables like GoChirp, have the potential to augment individual's sensory and cognitive capabilities, enabling a deeper connection with the natural environment. This could further enhance users' well-being and potentially foster a greater sense of responsibility towards the natural environment, leading to mutual benefits between humans and nature.

Indexed as

Wearable Electronic DevicesAdultAnimalsArtificial IntelligenceBirdsFemaleHumansMachine LearningMaleMiddle AgedNatureSurveys and QuestionnairesUrbanizationYoung Adult

Identifiers

PMID39774277
PMCPMC11707274

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.