Collecting Respiratory Sound Samples From Corona Patients to Extend the Diagnostic Capability of VOQX Electronic Stethoscope to Diagnose COVID-19 Patients
Technological developments in the recent decades has enabled the integration of electronic and digital components in the stethoscope design, in an attempt to improve auditory performance and, moreover, to assist in improving user's diagnostic accuracy by incorporating computerized, digital technologies, artificial intelligence capabilities and deep-learning-based algorithms enhancing these devices.
We believe that these technologies can be used to significantly improve the diagnostic performance in the primary care phase, by means of a sophisticated stethoscope that enables auscultation to sounds and signals typically found in the sub-sound frequency level. Their transformation into the sound range, and the use of artificial intelligence and machine learning techniques to characterize sound patterns that correspond to specific problems or diseases can substantially enhance the physician's or other care giver's performance to the benefit of the patients.
At this stage, the software in development does not purport to make diagnostic decisions, but only to provide information that will enhance decision and diagnosis making process, therefore enable a more accurate and definitive diagnostic decision and perhaps decrease the number of additional diagnostic tests requested.
調査の概要
詳細な説明
Up to 200 patients will participate in an open, prospective and multi-center study.
Patients diagnosed as positive to COVID-19 will be referred to a VOQX examination. All patients will receive detailed explanation about the purpose of the examination, its impact and will provide their consent prior to the examination. The VOQX device output will have no influence on the decision-making process of the physicians and care givers. The VOQX Stethoscope membrane will be put on the patient's chest area in predefined anterior and posterior points. The data collected in the form of breath sound signals in particular infra-sound will be transferred to an external computer and processed by machine learning algorithm developed by the company. The algorithm will seek patterns typical for the diagnosed disease for each corresponding case diagnosed.
研究の種類
入学 (予想される)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Hadas Sapir
- 電話番号：972 54 7826543
- メール：shadas@gsap.co.il
研究場所
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Ashkelon、イスラエル、7830604
- 募集
- Barzilai Medical Center
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Hadera、イスラエル、38100
- 募集
- Hille Yaffe Medical Center
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Zrifin、イスラエル、703000
- 募集
- Shamir Medical Center (Assaf Harofah)
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-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
- Patients over the age of 18 years
- RT-PCR positive for COVID 19
Patients diagnosed with the following pulmonary pathology:
- Pneumonia
- Pulmonary edema
- Bronchitis
- Acute asthmatic attack
- Emphysema
- Or Normal (e.g. asymptomatic patients)
The diagnosis is confirmed if possible, by:
- Anamnesis
- Physical examination
- X-ray
- Suggestive blood test - CBC
- Pulse oximetry
Exclusion Criteria:
- Pregnant women
- Chest malformation
- Unconsciousness
- Subject that need a guardian
- Weigh above 150 Kg.
- Patients with current shortness of breath
- Patients currently assisted by breathing machine such as CPAP or other
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ふるい分け
- 割り当て：なし
- 介入モデル：単一グループの割り当て
- マスキング：なし（オープンラベル）
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
|
実験的：Open Label
Up to 200 patients will participate in this open study. Before each examination with the study device, data from each patient (Current medical condition, medical history and demographic data) will be inserted to a computer and added to the database of the study for further processing in conjunction with the study device results. The study device electronic stethoscope membrane will be put on the patient's chest area in predefined anterior and posterior points. At the end of each examination the data will be transferred to a computer and stored in the patient's file. Each patient will be requested to attend the examination once. |
Electronic stethoscope
他の名前：
|
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Performance outcome
時間枠：Through study completion, an average of 1 year
|
Detection and identification of pulmonary sound signals ranging from infra-sound to auditory sound which are typical to specific pathologies of COVID-19
|
Through study completion, an average of 1 year
|
|
Performance outcome
時間枠：through study completion, an average of 1 year
|
Use machine learning technologies to identify the above sound patterns and corresponding pathologies
|
through study completion, an average of 1 year
|
協力者と研究者
スポンサー
捜査官
- スタディディレクター：David Linhard、Sanolla
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (予想される)
研究の完了 (予想される)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
追加の関連 MeSH 用語
その他の研究ID番号
- VOQX
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
米国で製造され、米国から輸出された製品。
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