TOUCHSIGHT PLATFORM

從鏡頭到 AI,
一套系統串起來。
From camera to AI —
one connected system.

WiFi 鏡頭看見人和探頭,WiFi 探頭回報是否真的接觸;你網路裡的邊緣節點把肌群輪廓疊到畫面上。MyoNav APP 帶你掃描,AI 助理把口語描述對應到身體部位。 A WiFi camera sees the person and the probe, a WiFi probe reports real contact, and an edge node on your own network overlays muscle outlines on the view. The MyoNav app guides the sweep; the AI assistant maps plain-language descriptions to body regions.

封閉測試 · 硬體開發中Closed beta · hardware in development
TouchSight system map: WiFi camera and WiFi probe send to an edge node on the local network; the app shows the overlay; the cloud API serves the AI assistant and database. 你的區網 · 影像不離開YOUR LOCAL NETWORK · VIDEO STAYS HERE 雲端 · 不含影像CLOUD · NO VIDEO WiFi 鏡頭WiFi camera 看整個人+探頭sees body + probe WiFi 探頭WiFi probe 壓力確認接觸pressure = contact 邊緣節點Edge node 姿勢+探頭定位pose + probe 肌群疊圖muscle overlay MyoNav APP 手機・平板・電腦phone · tablet · PC 雲端 APICloud API Cloud Run AI 助理AI assistant 帳號・資料庫Accounts · DB RTSP UDP WS HTTPS

實線在區網內;虛線才會連到雲端,而且不帶影像與人體骨架點。Solid lines stay on your network; only the dashed lines reach the cloud — without video or body landmarks.

COMPONENTS

四個部分,拆開也能用Four parts that also work on their own

每一層沒連上時,上一層照樣運作:沒有鏡頭就用 APP 單機導航,沒有雲端就在區網內完成疊圖。If a layer is missing, the one above keeps working: no camera, use the app standalone; no cloud, the overlay still runs on your network.

01

WiFi 鏡頭WiFi camera

固定在腳架上,拍下整個人與探頭;只負責串流,不在鏡頭端做任何判斷。On a tripod, it films the whole person and the probe. It only streams — no decisions are made on the camera.

  • 手機 RTSP 串流,或 Raspberry Pi 鏡頭模組Phone RTSP stream or a Raspberry Pi camera module
  • 設計目標 720p 30 fps,2.4 GHz WiFiTarget 720p at 30 fps over 2.4 GHz WiFi
開發中In development
02

WiFi 探頭WiFi probe

三個壓力感測器判斷是否真的貼在皮膚上,連同電量與訊號強度一起無線回報。Three pressure sensors tell whether it is really on the skin, reported wirelessly with battery and signal strength.

  • RP2040 感測板+ESP32-S3 無線橋接RP2040 sensor board + ESP32-S3 wireless bridge
  • 外殼貼有定位標籤,讓鏡頭找到探頭A fiducial tag on the shell lets the camera find it
開發中In development
03

邊緣節點Edge node

放在同一個網路裡的電腦:辨識人體姿勢與探頭位置,把肌群輪廓對到畫面上,再判斷這一刻能不能計入覆蓋。A computer on the same network finds body pose and probe position, aligns muscle outlines to the view, and decides whether this moment can count toward coverage.

  • 平板輸入 6 碼配對,免帳號Pair a tablet with a 6-digit code, no account
  • 約每秒 10 次更新疊圖Overlay updates about 10 times per second
封閉測試Beta
04

APP 與雲端App & cloud

MyoNav APP 顯示 3D 肌群、掃描路線與疊圖;登入後同步紀錄,並可使用 AI 助理。The MyoNav app shows 3D muscles, sweep paths and the overlay; signed-in users sync records and can use the AI assistant.

  • 帳號與資料庫:Supabase(東京)Accounts & database: Supabase (Tokyo)
  • API:Google Cloud RunAPI: Google Cloud Run
APP 已完成App available 看 APP →See the app →
DATA FLOW

一次掃描,資料怎麼流動What happens during one sweep

只有在鏡頭看得清楚、而且探頭確實接觸時,覆蓋才會往前走。Coverage only advances when the camera sees clearly and the probe is really in contact.

STEP 1

串流Stream

鏡頭把畫面、探頭把壓力與電量,經 WiFi 送到邊緣節點。The camera sends video and the probe sends pressure and battery over WiFi to the edge node.

區網LOCAL
STEP 2

定位Locate

辨識人體姿勢與探頭上的標籤,算出探頭在身上的位置。Body pose and the probe's tag are detected to place the probe on the body.

區網LOCAL
STEP 3

疊圖Overlay

把選定肌群的輪廓對到畫面上,並給一個信心燈號。The chosen muscle outline is aligned to the view with a confidence badge.

區網LOCAL
STEP 4

確認接觸Confirm contact

壓力感測確認貼合;按太大力或感測飽和時,改標為「未知」。Pressure sensors confirm contact; pressing too hard or saturating marks it as “unknown”.

區網LOCAL
STEP 5

覆蓋與紀錄Coverage & record

APP 即時畫出掃過的表面;登入時,只有摘要會同步到雲端。The app paints covered surface live; when signed in, only a summary syncs to the cloud.

APP → 雲端APP → CLOUD
GOOD

看得清楚、位置可信:顯示肌群輪廓,探頭接觸時計入覆蓋。Clear view, trusted position: outline shown, coverage counts while the probe is in contact.

LOW

光線不足、姿勢晃動或轉身:只給提示,不計入覆蓋,並告訴你原因。Low light, movement or turned away: hints only, no coverage, with the reason shown.

UNAVAILABLE

鏡頭斷線、人或探頭離開畫面:超過 1 秒沒有新畫面就停止疊圖,不沿用舊結果。Camera dropped, person or probe out of view: after one second without a new frame the overlay stops — stale results are never reused.

影像不離開你的網路。Video never leaves your network. 鏡頭畫面只在區網的邊緣節點處理;送到 APP 的是肌群輪廓與位置摘要,送到雲端的只有不含影像、不含人體骨架點的紀錄。 Camera frames are processed only on the local edge node. The app receives outlines and a position summary; the cloud receives records with no images and no body landmarks.
TESTED BEFORE HARDWARE

硬體到位前,先跑過每種狀況Every failure mode, rehearsed before the hardware arrives

用真實的邊緣節點程式,搭配模擬的鏡頭畫面與探頭訊號,在手機與平板模擬器上實際操作 APP。The real edge-node software, fed with simulated camera frames and probe signals, driven through the app on phone and tablet emulators.

13
SCENARIOS設備傳輸情境全數通過transmission scenarios passed
6
DEVICE PROFILES手機與平板直橫向phone & tablet, portrait + landscape
60fps
SMOOTHNESS操作時畫面更新中位數median frame rate while in use
0
LEAKS影像或骨架點外流次數video or landmark leaks
WiFi 掉包 5%5% WiFi packet loss WiFi 瞬斷 1.5 秒1.5 s WiFi dropout 探頭離線Probe offline 鏡頭斷線Camera dropout 人走出畫面Person leaves frame 探頭離開視野Probe out of view 光線變暗Low light 轉身Turned away 姿勢晃動Unstable pose 按壓過大Sensor saturation 低電量、訊號轉弱Low battery, weak signal 多重狀況同時發生Combined stress

以上為 2026 年 9 月的軟體模擬測試結果,使用合成畫面與模擬訊號,不是臨床量測,也不代表實機表現;實機驗證完成後會更新。 Software simulation results from September 2026 using synthetic frames and simulated signals. Not clinical measurements and not a statement of hardware performance; will be updated after hardware validation.

SYSTEM STATUS

系統狀態System status

官網Website
運作中Online
資料庫Database
已連線Connected
雲端 APICloud API
建置中Coming soon
AI 助理AI assistant
建置中Coming soon
MyoNav APP
封閉測試Closed beta
WiFi 鏡頭・探頭WiFi camera · probe
開發中In development

邊緣節點在你的網路裡,官網看不到它;配對後的連線狀態請在 APP 內查看。The edge node lives on your network, so this site can't see it — check its connection inside the app after pairing.

EARLY ACCESS

想在診間或團隊裡試用?Want to try it with your clinic or team?

目前採邀請制封閉測試。留下信箱,開放名額時會寄試用連結與安裝說明給你。We're in an invitation-only beta. Leave your email and we'll send a link and install guide when a spot opens.