Feasibility Trial of the Womb Watch Smartphone App To Assess Fetal Movements

NCT07626112 | Not Yet Recruiting FDA Device

• 2 other identifiers: STUDY00009098FP00014631
• Study Type: observational
• Target: 60
• Locations: 1 country
• Sites: 3

Brief Summary

The surveillance of pregnancies at risk for fetal loss secondary to high-risk maternal or fetal conditions remains a mainstay of perinatal care. Current testing to prevent fetal loss includes the regular use of ultrasound (biophysical profile) or fetal heart rate monitoring (non-stress test) in an outpatient clinic setting once or twice weekly. A patient may also be asked to subjectively assess daily fetal movements during the time between routine antepartum testing appointments. However, there are no good systems for pregnant women to objectively measure fetal movements. Smartphones have allowed for the development of applications that utilize various embedded devices including the camera and microphone. In our recent pilot STUDY00001552 of 205 pregnant patients, placement of the iPhone10 microphone directly on the maternal abdominal wall was utilized to detect fetal movements. AI assessment of the audio recordings proved superior to maternal perception of fetal movements that were recorded during simultaneous ultrasound (gross fetal movements: 64% audio vs 18% maternal; breathing: 93% vs 3%, hiccups: 73% vs 3%). This trial is a prospective, observational, feasibility study of 60 patients that includes both low-risk and high-risk pregnant women to examine the usability of the Womb Watch smartphone application. The study will involve introduction of the Womb Watch app to a population of pregnant patients. Features of the app will be modified based on participant feedback. Anxiety levels of the patient will be tracked serially using a survey tool. The various types and versions of smartphones will be assessed to see if they affect the AI model. Finally, patients will be asked to determine the strength of fetal movements to see if this parameter can be assessed by the AI model. Amniotic fluid data will assessed through clinical ultrasounds to see if this also has any effect on the AI model's ability to detect fetal movements.

Conditions

Assessment of Fetal Movement; Pregnancy; Pregnancy Complications; Stillbirth; Stillbirth and Neonatal Mortality; Fetal Movement; Pregnancy Complications Affecting Fetus (Diagnosis)

Keywords

fetal movement; stillbirth; pregnancy; decreased fetal movement; IUFD; fetal demise; fetal kick counting; antenatal testing

Outcome Measures

Primary Outcomes (1)

• Feasibility of Fetal Movement Assessment Using Pilot Womb Watch Smartphone Application

  Audio signals from different models and brands of smartphones with or without smartphone cases will be compared in our AI model. Participants using the pilot Womb Watch smartphone application will receive feedback on fetal movement assessment and help researchers determine if the application needs to be modified for real-world use.

  From July 2026 to September 2027

Secondary Outcomes (7)

• Fetal Gross Movement Assessment

  From the time of enrollment at 28 to 32 weeks' gestation, up until delivery. Kick counts and gross motor movements will be assessed daily.

• Fetal Breathing

  From the time of enrollment at 28 to 32 weeks' gestation, up until delivery. Kick counts and gross motor movements will be assessed daily.

• Fetal Hiccups

  From the time of enrollment at 28 to 32 weeks' gestation, up until delivery. Fetal hiccups will be assessed daily.

• Fetal Movement Intensity

  From the time of enrollment at 28 to 32 weeks' gestation, up until delivery. The Likert scale coincide with daily recordings made by the participant.

• Amniotic Fluid Index

  From the time of enrollment at 28 to 32 weeks' gestation, up until delivery. AFI will be assessed only after a participant has an ultrasound as part of their routine pregnancy care.

Study Arms (1)

Single Group Assignment

Pregnant women between 28 - 40 weeks gestation will record sounds coming from their pregnant abdomen daily for 15 minutes with the Womb Watch smartphone application. Participants must have a singleton intrauterine pregnancy, diagnosed as a low-risk or high-risk pregnancy, no prior diagnosis of an anxiety mood disorder or a psychiatric illness, access to the internet, a functioning email address, owns a personal smartphone, and be English speaking.

Device: Smartphone Application

Interventions

Smartphone Application DEVICE

Pregnant women between 28 - 40 weeks gestation will audio daily for 15 minutes using their personal smartphone with upload to the Womb Watch app. The microphone of the smartphone will be placed against the pregnant uterus. The audio files will be uploaded from the Womb Watch app via Google Firestore to an encrypted database at the Texas Advanced Computing Center (TACC-UT Austin). After the audio recording is uploaded, participants will be asked to assess the strength of fetal movements using a Likert scale in the app. Artificial intelligence will be employed to determine the number and strength of three categories of fetal movements: gross body movements, fetal breathing and fetal hiccups. Participants will receive the AI analysis regarding these movements through the customized app.

Single Group Assignment

Eligibility Criteria

• Age: 18 Years - 45 Years
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Pregnant women between 28 - 40 weeks of gestation with a singleton pregnancy.

You may qualify if:

• Ability to understand and voluntarily provide written signed informed consent to participate in the study.
• English speaking (the alpha version of the Womb Watch app is only available in English)
• Singleton intrauterine pregnancy
• Estimated gestational age at enrollment 28 weeks to 32 weeks
• Low-risk pregnancy with normal fetal growth and anatomy and no maternal co-morbidities of note.
• High-risk pregnancy including fetal anomalies and maternal co-morbidities including but not limited to cardiovascular, pulmonary, hepatic, renal, hematologic, gastrointestinal, endocrine/metabolic, immunologic, dermatologic, neurologic, or oncologic.
• No prior diagnosis of an anxiety mood disorder or a psychiatric illness
• Access to internet
• A functioning email address
• Owns personal smartphone; iPhone or Android of any generation

You may not qualify if:

• Currently pregnant with multiples (twins or more)
• Baseline GAD-7 score of 10 or more

Sponsors & Collaborators

• Kenneth Moise MD: lead
• The University of Texas Health Science Center, Houston: collaborator
• The University of Texas Medical Branch, Galveston: collaborator

Study Sites (3)

Dell Medical School- University of Texas at Austin

Austin, Texas, 78723, United States

Location

University of Texas Medical Branch at Galveston - UTMB Health

Galveston, Texas, 77555, United States

Location

McGovern Medical School - UTHealth Houston

Houston, Texas, 77030, United States

Location

Related Publications (1)

• Moise K Jr, Gaither K, Madden-Rusnak A, Lowry K, Hutson E, Bruns D, Valero R. Smartphone Detection of Fetal Movements Using Artificial Intelligence. Obstet Gynecol. 2026 May 1;147(5):616-623. doi: 10.1097/AOG.0000000000006228. Epub 2026 Mar 5.

  PMID: 41990345 BACKGROUND

MeSH Terms

Conditions

Pregnancy Complications; Disease; Stillbirth; Fetal Death

Condition Hierarchy (Ancestors)

Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Death

Central Study Contacts

Kenneth Moise, MD

CONTACT

713-444-7603; kmoise@austin.utexas.edu

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Professor of Women's Health

Study Record Dates

• First Submitted: May 23, 2026
• First Posted: June 4, 2026
• Study Start (Estimated): July 1, 2026
• Primary Completion (Estimated): September 30, 2027
• Study Completion (Estimated): September 30, 2027
• Last Updated: June 4, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (3)